predictors of successful adoption of technology supported
TRANSCRIPT
The African Journal of Information Systems The African Journal of Information Systems
Volume 13 Issue 2 Article 3
June 2021
Predictors of Successful Adoption of Technology Supported Predictors of Successful Adoption of Technology Supported
Learning in Universities in Uganda A Studentsrsquo Perspective Learning in Universities in Uganda A Studentsrsquo Perspective
Esther Namirembe Makerere University frixie2002usyahoocom
Michael Eddie Kyobe Prof University of Cape Town MichaelKyobeuctacza
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Part of the Engineering Commons and the Management Information Systems Commons
Recommended Citation Recommended Citation Namirembe Esther and Kyobe Michael Eddie Prof (2021) Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective The African Journal of Information Systems Vol 13 Iss 2 Article 3 Available at httpsdigitalcommonskennesaweduajisvol13iss23
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Predictors of Successful Adoption of Technology Supported Learning in Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective Universities in Uganda A Studentsrsquo Perspective
Cover Page Footnote Cover Page Footnote The researchers want to thank the Almighty God for the gift of knowledge wisdom and understanding in the writing of this paper The researchers also thank the Organization for Women in Science for the Developing World (OWSD) and the Swedish International Development Agency (SIDA) for their financial support in carrying out the study
This article is available in The African Journal of Information Systems httpsdigitalcommonskennesaweduajisvol13iss23
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 183
Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
Research Paper
Volume 13 Issue 2 June 2021 ISSN 1936-0282
Esther Namirembe
Makerere University
frixie2002usyahoocom
Michael Kyobe
University of Cape Town
MichaelKyobeuctacza
(Received August 2020 accepted January2021)
ABSTRACT
This study identified the predictors of successful adoption of technology supported learning (TSL)
among students in universities Presumably the perspective of the students in understanding this study is
crucial because students are key users of TSL systems and are faced with challenges in the adoption of
such systems in learning institutions We argue in the present study that predictors can be identified
using Gestalts approach given the complex interactions between the organizational and individual
factors The extent of interaction between the factors was accomplished using the clustering algorithm
Data was collected from 184 students from Makerere and Gulu universities Six clusters emerged out of
the findings of which Cluster 4 students adopted TSL the most These students indicated that successful
adoption of TSL is best achieved when there is coherence between financial support and when they are
in their second year of study
Keywords
Predictors technology supported learning universities Uganda Gestalts approach
INTRODUCTION
Predictors can be regarded as factors In this paper they are regarded as factors required for successful
adoption of technology-supported learning (TSL) These predictors can be categorized as organizational
and individual factors In this paper organizational factors are operationalized as the availability of the
goals of the university TSL policy time to experiment with information and communication technology
(ICT) financial support and commitment of university management With regard to this paper
individual factors are operationalized as age gender and level of education Whereas it has been
established that there are predictors that contribute to successful adoption of TSL there is growing
concern that if such predictors are not investigated adoption of TSL information systems (ISs) may
continue to be a challenge
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 184
Universities in developing economies in particular have adopted technology-supported learning
information systems (TSL ISs) to boost the knowledge society (Tchamyou 2017) Since students are the
key users of TSL (Bhardwaj amp Goundar 2018) in universities understanding their perspective in the
adoption of TSL would be paramount to educational re-engineering In addition students face
challenges during their encounter with TSL (Gerasimova et al 2018) They indicate that such
challenges or factors include lack of self-discipline and motivation financial implications and lack of
face to face interaction with a tutor Given the fact that these factors in adoption of TSL have a great
impact on students it is worth investigating such factors to augment their (studentsrsquo) learning in
universities
Other writers have reported disparities in who uses technology and at what age they are exposed to it In
order to understand the predictors of adoption and effective use of technology in education the
perspective of students regarding the adoption of technology and their views about what the institutions
should provide to make this adoption possible is critical However not many studies have looked at this
problem from the perspective of students who happen to use the TSL (Acosta et al 2018) In the present
study the researchers investigate the predictors of successful adoption of TSL as perceived by students
The Gestalts approach was adopted given the fact that the predictors are complex and interactional
making it difficult to measure their influence Gestalts is defined as configuration of institutional
components that has achieved a satisfactory high level of coherence (Venkatraman 1989) Gestalts
scholars argue that success is only achieved when the components achieve a satisfactorily high level of
coherence
The present study focuses on two categories of predictors organizational and individual factors The
next section reviews these predictors and how they interact to influence the adoption of TSL A
conceptual framework based on the Gestalts approach is developed and tested with a sample of students
from two institutions of learning in Uganda An elaboration about the approach used in this paper is in
the methodological framework Following this is the results and analysis and then discussion of
findings This paper ends with a conclusion
LITERATURE REVIEW
Definition of Technology-Supported Learning
The change from the traditional curriculum to the digital curriculum has revolutionalized higher
education Technology-supported learning has been defined and measured from different perspectives
by researchers Technology-supported learning has been defined by Hardaker and Singh (2011) ldquoas an
innovation situated in the interplay between structure and individual and how this leads to adoption and
diffusionrdquo (p222) Eze et al (2018) have defined TSL as technology-mediated learning that uses
hardware and software systems to enhance the teaching and learning processes Ayele amp Birhanie
(2018) indicate that TSL is a modern way of delivering learning resources to students in higher learning
institutions In this paper we choose to define TSL as e-learning resulting from the interaction between
the organizational and individual factors Gerasimova et al (2018) elaborates that TSL saves studentsrsquo
time and also reduces travel time associated with the traditional face to face approach TSL may
encompass compact disc read-only-memory (CD-ROMs) digital texts podcasts learning management
systems (LMSs) video-technology and websites among others
While CD-ROMs are no longer used widely today Kisanga and Ireson (2015) indicated at that time that
they were a very reliable way of accessing content by students Digital texts and podcasts have been
presented as vital tools for student knowledge delivery in the medical field (Back et al 2019) Learning
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 185
management systems also play a vital role in the delivery of academic resources to students in
universities (Gwamba et al 2018) Bond et al (2018) indicate that LMSs are commonly used among
students in higher education institutions in Germany Nevertheless a recent study by Kim et al (2019)
indicated that students had no experience with LMSs and video technology Chopra et al (2019)
indicate that students are satisfied with web-based learning
Organizational Factors and Technology-Supported Learning
Organizational factors such as management support user training and financial incentives increase the
adoption of TSL ISs in organizations (Ayele amp Birhanie 2018) Shah and Cheng (2019) argue that
development of TSL policies is an opportunity of revolutionizing universities while engaging students
Back et al (2019) suggest that students should practice with ICTs A study by The and Usagawa (2018)
revealed that if a person practices with ICTs they gain confidence in using such tools Shah and Cheng
(2019) similarly indicate that distance learners are faced with many challenges which may force them to
drop out of universities The students cited juggling work and study caring for children financial
difficulty and academic writing among others as challenges to TSL
Another area of concern raised by Shah and Cheng (2019) was the time spent by a student studying off-
campus Such time involves experimenting with ICTs Furthermore they argue that indicators such as
online learning resources relevant course materials and building student confidence are key to positive
learning Students perceive that commitment of university management in uploading the online
resources subscribing to relevant courses and ensuring that the lecturers build confidence in them
contributes to the adoption of TSL
Students perceived that organizational support plays a vital role in their adoption of TSL (Selim 2007)
A study by Bhardwaj and Goundar (2018) reveals that students perceive that university management
does not support their use of TSL We choose to look at the goal of the TSL policy time to experiment
with ICT financial support and commitment of university management as organizational factors that
can influence studentsrsquo adoption of TSL Additionally Moakofhi et al (2017) argue that studying
organizational factors is essential in understanding technological adoption
Individual Factors and Technology-Supported Learning
Individual factors can be termed as personal factors depending on the author The individual in question
is a student Kimiloglu et al (2017) specify that individual factors can explain the adoption of TSL ISs
Parlakkılıccedil (2014) indicated that age influences the use of information technologies In addition Pereira
et al (2018) uphold that people tend to adopt TSL at an early age Gerasimova et al (2018) specified
that the average age of students who adopted TSL at the Russian University of Economics was 23 years
They revealed that the majority of these students appreciated TSL Another study by Bhardwaj and
Goundar (2018) about studentsrsquo perceptions of TSL shows that the majority of the students engaged in
the study were aged between 21 to 30 years of age
With reference to gender female students showed a preference for humanities and social sciences while
their male counterparts preferred engineering natural science and ICT (Zuvic-Butorac et al 2011)
Nevertheless Kim et al (2019) report that female students are more experienced with TSL than males
Additionally Rhema and Miliszewska (2014) revealed that there is no difference between female and
male students when it comes to the acceptance of TSL in Libyan universities Furthermore Ramiacuterez-
Correa et al (2015) studied gender behavior in relation to the studentsrsquo acceptance of TSL in Chile and
Spain Their findings revealed that there is an insignificant difference between male and female students
in the use of TSL
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 186
The year of study of a student is perceived as the level of education in this paper As per the level of
education Damanpour and Schneider (2006) revealed that education level contributes to the adoption of
innovations Technology-supported learning is perceived as something new hence an innovation
Whereas many studies have been carried out on age and gender few studies seem to focus on the
contribution of level of education to the adoption of technological innovations and less so in developing
economies
It should be noted that the definition of TSL in this paper considers the interaction between
organizational and individual factors This implies that organizational factors impact the individual
factors in relation to the adoption of TSL and vice versa
Interaction between Factors of Adoption of Technology-Supported Learning and Their Impact on Technology Supported Learning
Scholars often wonder whether the individual (student) should adapt to the organization or whether the
organization (eg university) should adapt to the individual (Lippman 2013) Lippman observes that
debatably the preceding statements are incorrect It is better to ask ldquoHow do organizations shape the
individualrdquo In turn ldquoHow does the individual impact organizationsrdquo In his argument the university
can be composed of the students other individuals and the formal physical environment Singh et al
(2005) argue that the structure of organizations has changed They indicate that TSL is part and parcel of
the organization Organizational characteristics can impact on a studentsrsquo ability to adopt TSL
Universities are usually expected to provide policies time for interaction financial support and
commitment to the students in relation to the adoption of TSL (Shah amp Cheng 2019 The amp Usagawa
2018) Students have to be in harmony with the university mission in order for the university to achieve
organizational success University TSL policy gives structure to how students should learn assess and
improve their TSL skills in a university (Makerere University Council personal communication
January nd 2004) Maina and Njuki (2015) argue that organizational TSL policies influence the
adoption of TSL The Makerere University Council (personal communication September nd 2015)
highlights that TSL policies boost pedagogical practices and improve end user skills If students are
familiar with university TSL policies chances are high that their intention innovativeness and
acceptance of TSL will be high
The time students take in interacting with ICT is an important issue in learning environments (Salinas
2004) Drent and Meelissen (2008) argued that time can be assessed according to experimenting
interacting and reflecting with ICT Time has an impact on the adoption of TSL (Shah amp Cheng 2019)
among students Developing economies have been reported to have limited e-resources which reduces
individual ability to experiment with such resources The more students experiment with ICT the more
their intention to use innovativeness and acceptance of TSL
Universities are expected to assist students through financial support to boost their adoption of TSL
(Angolia amp Pagliari 2016) They indicate that TSL comes with new support requirements Additionally
they assert that financial support enhances adoption of TSL among students in higher education
institutions They highlight that in cases where institutions often purchase TSL facilities for the students
the TSL adoption rates tend to be high
University management should be committed to supporting students to boost their adoption of TSL
(Bhardwaj amp Goundar 2018) This can be achieved through training students on how to use TSL
facilities (Kim et al 2019) Students perceive that institutional support is one of the enablers for their
adoption of TSL (Okai-Ugbaje 2020)
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 187
According to Lippman (2013) studentsrsquo age gender and level of education influence their organizations
This can be observed through variations in the use of TSL policies in place time one takes interacting
with ICTs making use of resources and also participating in activities within an organization Literature
indicates that TSL policies are common within learning institutions (Drent amp Meelissen 2008) Students
can get acquainted with these policies take time to practise with ICT use acquired TSL facilities in the
university and avail themselves to receive information from university management about TSL
Whenever a new technology is adopted it finds a society with inequalities in terms of age gender and
level of education Thus understanding the impact of age gender and level of education in the adoption
of TSL in organizations is paramount Maina and Nzuki (2015) indicate that age is an important factor in
understanding adoption of innovations in learning organizations Pereira et al (2018) indicate that
adoption of technological innovations usually takes place at an early age Adewole-Odeshi (2014)
amplifies that older people tend to have low interaction with the learning organizations resulting in low
adoption of technological innovations in such organizations
The relationship between gender and different environments has been testified (Lee amp Pituch 2002
Martin 1991) Lee and Pituch (2002) suggested that gender should not be left out in information
technology (IT ) adoption models An early study by Martin (1991) on gender differences in technology
adoption and telephone use found that womenrsquos use of the telephone for socialization purposes helped
to expand its use in both residential and business areas Odewumi et al (2018) indicate that females are
disadvantaged when it comes to the adoption of information technology
Damanpour and Schneider (2006) reveal that education level is an individual factor They continue to
argue that education is an important aspect of the adoption of innovations Maina and Nzuki (2015)
agree that level of education impacts on the learning organization during the adoption of innovations In
some instances education is viewed as a management strategy that can ease implementation of specific
innovations in particular organizations (Ferreira et al 2015) There seems to be little research on how
the level of education impacts on the learning organization during the adoption of innovations this study
acted as a basis to fill the gap A first-year student may have no knowledge of the TSL policy in a
particular learning institution which may affect their use of TSL facilities
Theoretical Underpinnings of the Study
The interactions between organizational and individual factors have been presented indicating the
complexities involved These interactions were studied with different theoretical underpinnings Factors
can be studied from a theoretical point of view that seeks to predict TSL from both organizational
(macro) and individual (micro) perspectives (Hardaker amp Singh 2011) Sometimes referred to as the
ldquoduality of structurerdquo factors can be drawn from the works of Giddens lsquotheory of structurationrsquo who
argues that macro and micro perspectives are interlinked Giddens theory is mapped to that of (Rogers
2003)rsquos Diffusion of Innovations Theory to ensure that the factors of adoption of TSL are objectively
measured For instance individual (student) was operationalized according to factors of age gender and
level of education The concept of adoption of TSL has been operationalized as intention to use
innovative use and acceptance of TSL Students can perceive that the factors encourage the adoption of
TSL or not The factors that predict successful adoption of TSL have been studied by using the
conceptual framework in Figure 1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 188
Figure 1
The Conceptual Framework of Predictors of Successful Adoption of Technology- Supported
Learning (TSL) in Universities in Uganda
Gestalts Perspective in this Study
To represent the complex interactions we have incorporated Venkatraman (1989)rsquos Gestalts fit which is
an alignment perspective Venkatraman indicates that alignment aims at balancing related organizational
components This is usually done with the aim of achieving organizational success Gestalts fit has been
achieved by configuring factors that are unique tightly integrated and fairly stable We argue that
measuring organizational and individual factors using a linear model is not appropriate Thus alignment
as Gestalts was adopted to identify those configurations of organizational and individual factors that
predict the adoption of TSL in universities
If configurational factors of the framework (ie organizational and individual factors) are well aligned
then there is greater interaction and thus an increase in the adoption of TSL On the other hand if the
elements are misaligned the level of adoption of TSL is low Thus the following hypotheses were tested
by the researchers The greater the alignment between the organizational and individual factors the more
the i) intention to use ii) innovative use and iii) acceptance of TSL in universities will be
Table 1 provides the definitions of these factors In the conceptual framework the third element is an
outcome of the interaction or interplay between the first and second variables
Table 1
Factors Constructs Employed in the Study
Factors Constructs Operationalization References
Organization Goal of TSL policy availability of time
to experiment with ICT availability of
financial support and commitment of
management
Rogers 2003 Shah amp Cheng
(2019)
Individual (student) Student age gender and level of
education
Glazier et al (2019)
Alignment
Between 1 amp 2
Organization (1) Individual
(2)
Adoption of TSL
in universities in
Uganda (3)
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 189
Factors Constructs Operationalization References
Interaction The interaction between the main factors
ie organization and the individual
affect each other
Drazine amp Van de Ven (1985)
Perception This is the studentrsquos perspective that
indicates whether the factors encourage
adoption or not
Gerasimova et al (2018)
Alignment Level of coherence Venkatraman (1989)
Adoption of TSL Intention to use innovative use and
acceptance of TSL
Rogers (2003) Davis (1989)
METHODOLOGICAL FRAMEWORK
To investigate the predictors of the successful adoption of TSL among students the quantitative survey
mixed and cross-sectional research designs were used (Creswell 2014 Greene et al 1989) A recent
study by Shah and Cheng (2019) carried out on studentsrsquo perceptions used a quantitative research
design Thus the same design was adopted for this study In quantitative designs surveys are usually
used The researchers used a survey to collect data from a total of 184 students The survey was
structured into four main parts background information adoption of TSL organizational and individual
factors Bhardwaj and Goundar (2018) in their study on studentsrsquo perceptions on TSL used a mixed
research approach The researchers adopted the said research approach whereby the largely quantitative
and little qualitative techniques were used
Besides lecturers the population of study included students from both Makerere and Gulu universities
Students were chosen because they are the main users of TSL (Bhardwaj amp Goundar 2018) and they are
faced with challenges in using this type of learning (Gerasimova et al 2018) Purposive and simple
random sampling were used for quantitative data The given universities were purposively chosen
because of the level of knowledge and use of TSL Simple random sampling was used at departmental
level to collect quantitative data from students of agricultural sciences because they are among the main
users of TSL facilities at this level Purposive homogeneous sampling was used for qualitative data A
total of six students were interviewed to complement the questionnaire data
The study took place at a particular point in time hence it was cross-sectional in nature Internal and
external validity checks were used (Bhattacherjee 2012) Internal validity was achieved by omitting
extraneous variables so that changes in the response to variables is caused by the hypothesized
explanatory variables External validity was achieved by generalizing from Makerere and Gulu
universities to other universities These two universities were chosen because their lecturers have been
motivated earlier their students would have had more exposure to the technology adoption and with that
experience it would be appropriate to capture their perspectives Validity of the student qualitative
instrument was achieved through use of research experts who were used to validate whether the content
in the instrument could get the data required (Ozkan amp Koseler 2009)
Additionally the developed question concepts were derived from past relevant studies This can be
related to Bhardwaj and Goundar (2019) who captured studentsrsquo perceptions on TSL based on the
modification of concepts from relevant past studies Studies on studentsrsquo perceptions taking a
quantitative approach are usually carried out using reliability tests Kim et al (2019) carried out a
reliability test on a questionnaire that was administered to undergraduate students in a university in
Korea using Cronbachrsquos alpha Similarly the researchers used the same alpha to test questions in the
student self-administered questionnaire The outcome variable of the adoption of TSL was
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 190
operationalized as intention to use innovative use and acceptance of TSL with Cronbach alphas of 064
067 070 respectively The organizational factors had a Cronbach alpha of 073 The researchers
followed ethics guidelines to accomplish the study
RESULTS AND ANALYSIS
Background Information
The majority (821) of the students were aged between 21 and 30 years old This is in line with
Bhardwaj and Goundar (2018) who indicated that the majority of the student respondents were between
21 to 30 years old The majority (641) of the student respondents were male while 359 were female
respondents This is in line with Zuvic-Butorac et al (2011) who found that female students
concentrated on art subjects while their male counterparts were in engineering natural science and ICT
Most (410) of the students were in their second year of study followed by first year students (ie
320) The majority of the students (ie 940) had access to email Few (386) students had laptops
This is because these students may not be in position to afford such devices Most (592) of the
respondents revealed that there are functional TSL laboratories in their universities Most of the students
(571) were affiliated to Gulu University For descriptive analysis of means and standard deviations
for selected research variables see Tables 2 and 3 All the data simulations were based on a Likert scale
of 5 Descriptive analysis of the individual (student) presenting modal age gender and level of education
of the whole population of students (ie N =184) is shown in Table 3
Descriptive Statistics
Table 2
Descriptive Statistics for Selected Research Variables (N =184)
Variable Brief Description of Variables M a Min Max SD
Adoption of TSL
Intention to Use
ITU1 Computers 445 1 5 0979
ITU2 CD-ROMs 283 1 5 1468
ITU3 Web-based learning 384 1 5 1344
ITU4 Video conferencing 359 1 5 1449
ITU5 University TSL environments eg Black-Board 366 1 5 1425
Innovative Use
INU1 I am able to expound on what lecturers have provided to me in class using
the Internet
379 1 5 1334
INU2 I am able to make presentations in text audio and visual 380 1 5 1424
INU3 I am able to communicate with other students through online discussions
emails wikis and WhatsApp
371 1 5 1496
Acceptance
ACC1 Computers 452 1 5 0941
ACC2 CD-ROMs 296 1 5 1536
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 191
Variable Brief Description of Variables M a Min Max SD
ACC3 Web-based learning 375 1 5 1388
ACC4 Video conferencing 359 1 5 1376
ACC5 University TSL environments eg Black-Board 361 1 5 1536
Organizational Factors
GUELP1 Goal of university TSL policy 297 1 5 1408
ATIEXICT1 Availability of time to experiment with ICT 322 1 5 1366
AFS1 Availability of financial support 273 1 5 1544
COMAN1 Commitment of management 304 1 5 1362
a A score of 350 indicates that the person has and there was ldquoeg intention to use TSL encouragement
on use of TSL facilities and ldquohindrance to the progress of TSL ISsrdquo on the five-point Likert scale of
1(Very little or no intention to use TSL encouragement on use of TSL facilities and hindrance to the
progress of TSL ISs ) and 5(Very much intention to use TSL greatest encouragement on use of TSL
facilities and very much hindrance to the progress of TSL ISs)
Students had lsquomuchrsquo intention to use TSL facilities For instance they had lsquomuchrsquo intention to use
computers (ITU1) The students had lsquomuchrsquo innovative use of TSL (for instance they were able to make
presentations in text audio and video INU2) They also indicated very much acceptance of TSL For
instance they had very much acceptance of computers (ACC1)
See Table 3 for most frequent characteristics of each individual in the whole student population (ie N
=184)
Table 3
Individual Factors (N = 184)
Individual Factors Rate of Occurrence Most Frequent
Individual Factors
AGE Most frequent age of students 25 Years
GEN Most frequent gender of students Male
LEDUC Most frequent year of study of students Year 2
Cluster Analyses
The researchers used the k-means clustering algorithm with the help of Statistica Software version 133
to generate six clusters The data were standardized Whereas several simulations were carried out (ie1
2 3 4 5 and 6) only the sixth simulation showed acceptable results All 6 simulations yielded p values
less than 005 (see Table 4) Table 4 indicates the measurement of the organizational factors and
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 192
adoption of TSL in universities in Uganda across the six student clusters Table 5 shows the
measurement of the individual factors across the said clusters
Table 4
Cluster Analysis and Analysis of Variance for Students
Cluster
Variable 1
(n = 37)
2
(n = 38)
3
(n = 19)
4
(n = 42)
5
(n = 24)
6
(n = 24)
ANOVA
F p
Adoption of TSL
Intention to Use TSL
ITU1 011 024 002 032 048 -161 244 00
ITU2 -007 -074 033 069 -014 -005 1109 00
ITU3 -101 037 035 058 039 -072 2502 00
ITU4 -084 031 031 059 031 -079 1893 00
ITU5 -056 022 -006 059 029 -078 1159 00
Innovative Use of TSL
INU1 -025 051 -024 065 -013 -122 2075 00
INU2 014 029 -142 049 052 -092 2671 00
INU3 -051 044 -128 061 049 -045 2449 00
Acceptance of TSL
ACC1 023 023 007 039 034 -179 3439 00
ACC2 -021 -085 050 092 018 -052 2579 00
ACC3 -087 041 007 064 033 -081 2219 00
ACC4 -100 027 029 067 057 -086 3169 00
ACC5 -065 001 -013 064 066 -069 1529 00
Organizational Factors
GUELP1 004 032 -024 078 -099 -075 2078 00
ATIEXICT1 019 -051 -069 089 -009 -040 1636 00
AFS1 012 -051 -044 105 -053 -036 2228 00
COMAN1 001 -017 -057 074 -018 -039 835 00
Note Positive values are indicated in bold while negative ones are not in bold
Table 5
Individual Factors per Cluster
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
AGE Most frequent
age of
students
26
Years
25
Years
25
Years
25
Years
26
Years
24
Years
356 00
GEN Most frequent
gender of
students
Male Equal
number
of male
and
female
Female Male Male Male 426 00
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 193
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
LEDUC Most frequent
year of
study of
students
Year 2 Year 2 Year 1 Year 2 Year 4 Year 1 409 00
Qualitative Analysis
Thematic analysis was used in analyzing qualitative data We used Braun and Clarke (2006)rsquos six
thematic analysis steps of familiarization generating initial codes searching reviewing defining and
naming themes and producing a report Studentsrsquo data comprised student interview data items from
which initial extracts were made Familiarization was carried out by reading and re-reading the said data
items Generating initial codes was achieved through capturing features of interest from the student data
set Searching was achieved through grouping student data relevant to potential themes Defining and
naming was achieved by categorizing the themes Finally a report about the student data was produced
The researchers used the most significant interview data that could support the quantitative results
presented in this paper in the discussion of findings section Thus the discussion of findings is
integrative
DISCUSSION OF FINDINGS
In this section qualitative findings have been integrated with the quantitative ones The letter lsquoSrsquo
denotes student Cluster 1 students were ranked third as far as the adoption of TSL is concerned because
of the quite weak alignment between the configurational factors For instance the students had no
intention to use web-based technology This was confirmed by student S5 who revealed that she did not
understand web-based learning These students could not interact with their colleagues using TSL
facilities Students in this cluster never embraced video conferencing technology because it is limited as
reflected in the main themes by the students S1 S3 and S5 However these students had the intention to
use computer technology This is consistent with student S1 who commented that ldquoI have the intention
to use computers for academic purposesrdquo They also had innovative use of TSL shown through their
ability to incorporate text audio and visual technology Furthermore these students accepted computer
technology This is supported by students S1 S2 and S6 who revealed that they use computers because
of the current education trend which demands them to be computer literate for academic purposes and
they are easy to work with
Further analysis of this cluster indicates that the organizational factors encourage these students to use
TSL facilities (see Table 4) Qualitative results from students S1 S4 and S3 respectively had the
following implications on the organizational factors
bull the goal of the TSL learning policy encourages the use of TSL facilities at a minimal level
bull students practise with ICT and also believe that the university indirectly supports them financially by
providing limited wireless fidelity
bull the university management is supportive by designing sessions on how to use computers
A typical student in this cluster was 26 years old male by gender and in his second year of study (see
Table 5) While these students have similar characteristics with those of Cluster 6 they have tried to
adopt TSL facilities compared Cluster 6 students because of their experience with such facilities
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 194
Cluster 2 students ranked second as far as adoption of TSL is concerned For example students in this
cluster revealed lsquomuchrsquo intention to use TSL For instance student S1 confirmed that ldquoWeb-based
learning offers more informationrdquo Students in this cluster were lsquovery muchrsquo capable of expounding on
what lecturers had provided to them in class using the Internet This was through ldquosurfingrdquo the Internet
using the Google search engine as revealed by student S1 Students in this cluster had lsquomuchrsquo
acceptance of TSL facilities such as web-based facilities This is because web-based learning can be
used for research work and expounding on what is taught in class by lecturers as revealed by student S1
This is confirmed by a recent study by Chopra et al (2019) that indicates that students are satisfied by
web-based technology
In relation to the organizational factors students in Cluster 2 agreed that the goal of university TSL
policy encourages their use of TSL facilities The qualitative results suggest that e-discussions can
compel students to use TSL facilities as revealed by Student S3 On average students in this cluster
were aged 25 years the number of male students was equivalent to that of female ones and they were in
their second year of study (see Table 5) These students could be better adopters than those of Cluster 1
because they seemed to have an equal gender distribution Such distribution may account for an unequal
educational technology use among Cluster 1 and 2 students who enjoyed a similar learning experience
(see Tables 4 and 5) Students of this cluster seemed to be better adopters than those of Clusters 1 3 5
and 6 because of their ability to make use of the TSL policy to their advantage (see Tables 4 and 5)
Cluster 3 students were low adopters of TSL because of low alignment between the configurational
factors thus ranked fifth as far as adoption of TSL is concerned These students lacked innovative use of
TSL facilities implying that these students cannot use such facilities to improve their learning
capabilities The same students however registered lsquovery muchrsquo acceptance of CD-ROMs (see Table 4)
This could be because this medium is a dependable way of accessing content by students (Kisanga amp
Ireson 2015)
Students in Cluster 3 perceived that the organizational factors never contributed to their use of TSL
facilities in any way (see Table 4) For example students had no time to experiment with ICT This
could be because students never practise with ICT due to the fact that the course is ldquohecticrdquo and the IT
laboratories are usually closed over the weekend as revealed by student S1 The average age gender
and level of education of a student in this cluster is 25 years female and first-year respectively (see
Table 5) These could be lower adopters of TSL than members of Clusters 2 and 5 because of their
gender Female respondents are disadvantaged when it comes to the use of information technology
(Odewumi 2018) Another plausible reason for the low adoption levels in Cluster 3 compared to those
in Clusters 2 and 1 could be the lack of innovative use of TSL (see Table 4)
Cluster 4 students were the greatest adopters of TSL among the six clusters This is because they had the
lsquogreatestrsquo alignment between the configurational factors These students are eager to use ICT innovative
and embraced TSL They are eager to use CD-ROM technology because such technology is cheap and
stores information as confirmed by students S1 and S6 They can innovatively expound on what
lectures have provided to them in class using the Internet with the help of search engines (such as
Google) as indicated by student S1 They have embraced video conference technology Students S1 S3
and S5 confirmed that they were able to imitate the limited video conferencing learning using the
WhatsApp facility
Students in Cluster 4 perceived that the organizational factors encouraged their use of TSL facilities
High scores were registered on the goal of the university TSL policy time to experiment with ICT
financial support and commitment of university management For instance during the interview process
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 195
student S3 revealed that ldquoa discussion policy for example may improve adoption of [TSL] because
once e-discussions are made they can compel one to use the [TSL] facilitiesrdquo The result from the
interview process on time to experiment with TSL conflicts with the cluster one whereby the majority
of the students never found time to practise with TSL facilities Shah and Cheng (2019) however
indicate that time influences the adoption of TSL facilities Quantitative findings in this cluster on
financial support could be related to those of student S3 who indicated that there was indirect financial
support by their university through the provision of wireless technology On the issue of management
commitment findings are in line with those of student S4 who felt that university management was
committed because they designed computer literacy sessions for them A typical student in this cluster
was 25 years old male by gender and in year 2 of study (see Table 5) This cluster (n = 42) had the
majority of the student respondents among the six clusters
The alignment of the configurational factors in Cluster 5 seemed to be lsquoweakerrsquo than that of Cluster 1
thus this cluster was ranked fourth Whereas the students in this cluster indicated lsquovery muchrsquo adoption
of TSL in some instances the configurational variables registered low scores For instance they had
very much acceptance of TSL environments yet they seemed not to be familiar with the TSL policy
The result on acceptance of TSL environments is parallel to that of Bond et al (2018) who indicated that
such environments are commonly used by students in higher education institutions in Germany The
result on the TSL policy was confirmed by student S4 who revealed that the TSL policy is not
effectively implemented in the university A normal student in this cluster was 26 years old male by
gender and in year 4 of the study (see Table 5) These students could be better adopters of TSL than
those of Clusters 3 and 6 because of their long-time experience with TSL as reflected in their year of
study compared to the said clusters (see Tables 4 and 5) It is not surprising this cluster had the best
distributions of ICTs among students
Similar to Cluster 5 Cluster 6 had 24 respondents (see Table 4) However students in this cluster are
coincidentally ranked as non-adopters of TSL among the six clusters (see Tables 4 and 5) This is
because there is no alignment between the configurational factors resulting in no adoption of TSL
These students were not willing to use IT could not modify their learning capabilities using IT and had
not realised the value of IT tools All 24 respondents in this cluster lsquoconcurredrsquo that the organization
never encouraged their use of TSL facilities This could imply that students were not involved at all
during the adoption of TSL Shah and Cheng (2019) reveal that students perceive that juggling work and
study caring for children financial difficulty and academic writing among other factors affect their
ability to adopt TSL On average students in this cluster were 26 years old male by gender and in year
1 of their study Being in their first year of study could imply that they had little experience with TSL
CONCLUSION
Identification of predictors of successful adoption of TSL among students was achieved using the
Gestalts approach Students perceived that organizational and individual factors predict successful
adoption of TSL Cluster 4 is the most coherent and as such adopted TSL most This is because the
organizational and individual factors were most aligned For example when students in this cluster are
financially supported and are in their second year of study they are eager to use to be innovative with
and embrace TSL And because of their eagerness innovativeness and ability to embrace TSL they have
accumulated more experience than others Cluster 6 students are non-adopters because they are more
inexperienced with TSL than the rest of the students
There seems to be a gap in the use of the non-linear techniques (eg clustering technique) in studies on
studentsrsquo perceptions Most studies for instance Chopra et al (2019) Gerasimova et al (2018) and Shah
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 196
and Cheng (2019) who have measured student perceptions have used linear techniques Thus this study
has closed this gap This study is a benchmark for universities in developing economies to integrate TSL
at university level For instance it should be noted that in order to achieve successful adoption of TSL
among students in universities management must be involved Nabushawo et al (2018) suggest that the
commitment of management can be achieved by collaborating with and training the users of TSL ISs
Since the world is challenged by Corona Virus Disease (COVID) this study can be used as model to
avail learning materials to students without spreading this disease
It should be noted that the rate of adoption of TSL among students is still low yet they have advanced in
age This contradicts Pereira et al (2018) who indicated that adoption of TSL usually takes place at an
early age It is therefore recommended that students should be supported to adopt TSL during their
earlier career years so that universities in Uganda can benefit from this innovation This can be done by
introducing TSL at primary level Universities need to strengthen their management capabilities such as
increasing the time studentsrsquo have to experiment with ICTs Further research is required to develop
strategies that can be adopted to enhance adoption of TSL among students at earlier ages Although this
study was carried out at a particular point in time it can also be carried out longitudinally There are
many indicators of the organization individual (student) and adoption of TSL besides those presented in
the conceptual framework Further research can be carried out on those Besides organization and
individual factors there is need to know the role of other factors in the adoption of TSL among students
While students from only two public universities were considered for this study students from other
universities can be considered as well
ACKNOWLEDGMENTS
The researchers want to thank the Almighty God for the gift of knowledge wisdom and understanding
in the writing of this paper The researchers also thank the Organization for Women in Science for the
Developing World (OWSD) and the Swedish International Development Agency (SIDA) for their
financial support in carrying out the study
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Acosta M L Sisley A Ross J Brailsford I Bhargava A Jacobs R amp Anstice N (2018) Student acceptance of e-
learning methods in the laboratory class in optometry PLOS ONE 13(12) 1-15
httpsdoiorg101371journalpone0209004
Adewole-Odeshi E (2014) Attitude of students towards e-learning in South-West Nigerian universities An application of
technology acceptance model Library Philosophy and Practice Article 1035
Angolia M G amp Pagliari L R (2016) Factors for successful evolution and sustainability of quality distance education
Online Journal of Distance Learning Administration 19(3)
Ayele B A amp Birhanie W K (2018) Acceptance and use of e-learning systems The case of teachers in technology
institutes of Ethiopian universities Applied Informatics 5(1) 1-11 httpsdoiorg101186s40535-018-0048-7
Back D A von Malotky J Sostmann K Peters H Hube R amp Hoff E (2019) Experiences with using e-learning tools
in orthopedics in an uncontrolled field study application Orthopaedics amp Traumatology Surgery amp Research
105(2) 389-393 httpsdoiorg101016jotsr201901002
Bhardwaj A amp Goundar S (2018) Students perspective of elearning and the future of education with MOOCs
International Journal of Computer Engineering 7(5) 248-260
Bhattacherjee A (2012) Social science research Principles methods and practices Textbooks Collection
httpscholarcommonsusfeduoa_textbooks3
Bond M Mariacuten V I Dolch C Bedenlier S amp Zawacki-Ritcher O (2018) Digital transformation in German higher
education Student and teacher perceptions and usage of digital media International Journal of Educational
Technology in Higher Education 15(48) httpsdoiorg101186s41239-018-0130-1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 197
Braun V amp Clarke V (2006) Using thematic analysis in psychology Qualitative Research in Psychology 33 77-101
Chopra G Madan P Jaisingh P amp Bhaskar P (2019) Effectiveness of e-learning portal from studentsrsquo perspective A
structural equation model (SEM) approach Interactive Technology and Smart Education 16(2) 94-116
httpsdoiorg101108ITSE-05-2018-0027
Creswell J W (2014) Research Design Qualitative quantitative and mixed methods approaches (4th ed) Sage
Publications
Damanpour F amp Schneider M (2006) Phases of the adoption of innovation in organisations Effects of environment
organisation and top managers British Journal of Management 17 215ndash236 httpsdoiorg101111j1467-
8551200600498x
Davis F D (1989) Perceived usefulness perceived ease of use and user acceptance of information technology MIS
Quarterly 13(3) 319ndash340 httpsdoiorg102307249008
Drazin R amp Van de Ven A H (1985) Alternative forms of fit in contingency theory Administrative Science Quarterly
30(4) 514-539 httpsdoiorg1023072392695
Drent M amp Meelissen M (2008) Which factors obstruct or stimulate teacher educators to use ICT innovatively
Computers amp Education 51 187ndash199 httpsdoiorg101016jcompedu200705001
Eze S C Chinedu-Eze V C amp Bello A O (2018) The utilisation of e-learning facilities in the educational delivery
system of Nigeria A study of M-University International Journal of Educational Technology in Higher Education
15 (34) 1-20 httpsdoiorg101186s41239-018-0116-z
Ferreira A Teixeira A L amp Dantas A R (2015) Non-technological innovation activities mediate the impacts of the
intra- and extra-organisational contexts on technological innovation outputs Enterprise and Work Innovation
Studies 11 9-43
Gerasimova V G Melamud M R Tutaeva D R Romanova Y D amp Zhenova N A (2018) The adoption of e-learning
technology at the Faculty of Distance Learning of Plekhanov Russian University of Economics Journal of Social
Studies Education Research 9(2) 172-188
Glazier R A Hamann K Pollock P H amp B Wilson B M (2019) Age gender and student success Mixing face-to-face
and online courses in political science Journal of Political Science Education 16(2) 142-157 httpsdoiorg1010801551216920181515636
Greene J C Caracelli V J amp Graham W F (1989) Toward a conceptual framework for mixed method evaluation
designs Educational Evaluation and Policy Analysis 11(3) 255-274 httpsdoiorg1023071163620
Gwamba G Renken J Nampijja J Mayende G amp Muyinda P B (2018) Contextualisation of e-learning systems in
higher education institutions In M Auer amp T Tsiatsos (Eds) Interactive mobile communication technologies and
learning Proceedings of the 11th IMCL conference (pp 44-55) Springer
Hardaker G amp Singh G (2011) The adoption and diffusion of eLearning in UK universities A comparative case study
using Giddenss theory of structuration Campus-Wide Information Systems 28(4) 221ndash233
httpsdoiorg10110810650741111162707
Kim H J Hong A J amp Song H (2019) The roles of academic engagement and digital readiness in studentsrsquo
achievements in university e-learning environments International Journal of Educational Technology in Higher
Education 16(21) 1-18 httpsdoiorg101186s41239-019-0152-3
Kimiloglu H Ozturan M amp Kutlu B (2017) Perceptions about and attitude toward the usage of e-learning in corporate
training Computers in Human Behavior 72 339-349 httpsdoiorg101016jchb201702062
Kisanga D amp Ireson G (2015) Barriers and strategies on adoption of e-learning in Tanzanian higher learning institutions
Lessons for adopters International Journal of Education and Development using Information and Communication
Technology (IJEDICT) 11(2) 126-137
Lee Y-K amp Pituch K (2002 December 10ndash13) Moderators in the adoption of e-learning An investigation of the role of
gender [Article] The Second International Conference on Electronic Business Taipei Taiwan
Lippman P C (2010) Can the physical environment have an impact on the learning environment CELE Exchange
httpsdoiorg1017875km4g21wpwr1-en
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 198
Maina M K amp Nzuki D M (2015) Adoption determinants of e-learning management system in institutions of higher
learning in Kenya A case of selected universities in Nairobi metropolitan International Journal of Business and
Social Science 6(2) 233ndash248
Martin M (1991) The culture of the telephone In PD Hopkins (Ed) Sexmachine Readings in culture gender and
technology (pp 50-74) Indiana University Press
Moakofhi M Leteane O Phiri T Pholele T amp Sebalatlheng P (2017) Challenges of introducing e-learning at
Botswana University of Agriculture and Natural Resources Lecturersrsquo perspective International Journal of
Education and Development using ICT 13( 2) 4-20
Nabushawo H M Muyinda P B Isabwe G M N Prinz A amp Mayende G (2018) Improving online interaction among
blended distance learners at Makerere University In M E Auer D Guralnick amp I Simonics (Eds) Advances in
Intelligent Systems and Computing (pp 63-69) Springer httpsdoiorg101007978-3-319-73210-7_8
Odewumi M O Yusuf M O amp Oputa G O (2018) UTAUT model Intention to use social media for learning interactive
effect of postgraduate gender in South-West Nigeria International Journal of Education and Development using
Information and Communication Technology (IJEDICT) 14(3) 239-251
Okai-Ugbaje S Ardzejewska K amp Imran A (2020) Readiness roles and responsibilities of stakeholders for sustainable
mobile learning adoption in higher education Education Sciences 10(3) 49-69
httpsdoiorg103390educsci10030049
Ozkan S amp Koseler R (2009) Multi-dimensional studentsrsquo evaluation of e-learning systems in the higher education
context An empirical investigation Computers amp Education 53(4) 1285ndash1296
httpsdoiorg101016jcompedu200906011
Parlakkılıccedil A (2014) Change management in transition to e-learning system Qualitative and Quantitative Methods in
Libraries 3(3) 637ndash651
Pereira A Martins P Morgado L amp Fonseca B (2018) Technological proposal using virtual worlds to support
entrepreneurship education for primary school children In M E Auer D Guralnick amp I Simonics (Eds)
Advances in Intelligent Systems and Computing (pp 124-132) Springer
Ramiacuterez-Correa P E Arenas-Gaitaacuten J amp Rondaacuten-Cataluntildea F J (2015) Gender and acceptance of e-learning A multi-
group analysis based on a structural equation model among college students in Chile and Spain PLOS ONE
10(10) 1-17 httpsdoiorg101371journalpone0140460
Rhema A amp Miliszewska I (2014) Analysis of student attitudes towards e-learning The case of engineering students in
Libya Issues in Informing Science and Information Technology 11 169-190 httpsdoiorg10289451987
Rogers E M (2003) Diffusion of innovations (5th ed) Free Press
Salinas J (2004) Cambios metodoloacutegicos con las TIC Estrategias didaacutecticas y entornos virtuales de ensentildeanza-aprendizaje
Bordoacuten 56(3-4) 469-481
Selim H M (2007) Critical success factors for e-learning acceptance Confirmatory factor models Computers amp
Education 49(2) 396ndash413 httpsdoi101016jcompedu200509004
Shah M amp Cheng M (2019) Exploring factors impacting student engagement in open access courses Open learning The
Journal of Open Distance and E-Learning 34(2) 187-202 httpsdoiorg1010800268051320181508337
Singh G ODonoghue J amp Worton H (2005) A study into the effects of elearning on higher education Journal of
University Teaching and Learning Practice 2(1) 13-24
Tchamyou V S (2017) The role of knowledge economy in African business Journal of the Knowledge Economy 8(4)
1189ndash1228 httpsdoiorg101007s13132-016-0417-1
The M M amp Usagawa T (2018) A comparative study of studentsrsquo readiness on e-learning education between Indonesia
and Myanmar American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS) 40(1)
113-124
Venkatraman N (1989) The concept of fit in strategy research Toward verbal and statistical correspondence Academy of
Management Review 9(3) 513-525 httpsdoiorg102307258177
Zuvic-Butorac M Nebic Z amp Nemcanin D (2011) Establishing an institutional framework for an e-learning
implementation Experiences from the University of Rijeka Croatia Journal of Information Technology Education
Innovations in Practice 10 43-56 httpsdoiorg10289451364
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Recommended Citation
-
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Cover Page Footnote
-
- tmp1624440487pdfGS9c9
-
Predictors of Successful Adoption of Technology Supported Learning in Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective Universities in Uganda A Studentsrsquo Perspective
Cover Page Footnote Cover Page Footnote The researchers want to thank the Almighty God for the gift of knowledge wisdom and understanding in the writing of this paper The researchers also thank the Organization for Women in Science for the Developing World (OWSD) and the Swedish International Development Agency (SIDA) for their financial support in carrying out the study
This article is available in The African Journal of Information Systems httpsdigitalcommonskennesaweduajisvol13iss23
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 183
Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
Research Paper
Volume 13 Issue 2 June 2021 ISSN 1936-0282
Esther Namirembe
Makerere University
frixie2002usyahoocom
Michael Kyobe
University of Cape Town
MichaelKyobeuctacza
(Received August 2020 accepted January2021)
ABSTRACT
This study identified the predictors of successful adoption of technology supported learning (TSL)
among students in universities Presumably the perspective of the students in understanding this study is
crucial because students are key users of TSL systems and are faced with challenges in the adoption of
such systems in learning institutions We argue in the present study that predictors can be identified
using Gestalts approach given the complex interactions between the organizational and individual
factors The extent of interaction between the factors was accomplished using the clustering algorithm
Data was collected from 184 students from Makerere and Gulu universities Six clusters emerged out of
the findings of which Cluster 4 students adopted TSL the most These students indicated that successful
adoption of TSL is best achieved when there is coherence between financial support and when they are
in their second year of study
Keywords
Predictors technology supported learning universities Uganda Gestalts approach
INTRODUCTION
Predictors can be regarded as factors In this paper they are regarded as factors required for successful
adoption of technology-supported learning (TSL) These predictors can be categorized as organizational
and individual factors In this paper organizational factors are operationalized as the availability of the
goals of the university TSL policy time to experiment with information and communication technology
(ICT) financial support and commitment of university management With regard to this paper
individual factors are operationalized as age gender and level of education Whereas it has been
established that there are predictors that contribute to successful adoption of TSL there is growing
concern that if such predictors are not investigated adoption of TSL information systems (ISs) may
continue to be a challenge
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 184
Universities in developing economies in particular have adopted technology-supported learning
information systems (TSL ISs) to boost the knowledge society (Tchamyou 2017) Since students are the
key users of TSL (Bhardwaj amp Goundar 2018) in universities understanding their perspective in the
adoption of TSL would be paramount to educational re-engineering In addition students face
challenges during their encounter with TSL (Gerasimova et al 2018) They indicate that such
challenges or factors include lack of self-discipline and motivation financial implications and lack of
face to face interaction with a tutor Given the fact that these factors in adoption of TSL have a great
impact on students it is worth investigating such factors to augment their (studentsrsquo) learning in
universities
Other writers have reported disparities in who uses technology and at what age they are exposed to it In
order to understand the predictors of adoption and effective use of technology in education the
perspective of students regarding the adoption of technology and their views about what the institutions
should provide to make this adoption possible is critical However not many studies have looked at this
problem from the perspective of students who happen to use the TSL (Acosta et al 2018) In the present
study the researchers investigate the predictors of successful adoption of TSL as perceived by students
The Gestalts approach was adopted given the fact that the predictors are complex and interactional
making it difficult to measure their influence Gestalts is defined as configuration of institutional
components that has achieved a satisfactory high level of coherence (Venkatraman 1989) Gestalts
scholars argue that success is only achieved when the components achieve a satisfactorily high level of
coherence
The present study focuses on two categories of predictors organizational and individual factors The
next section reviews these predictors and how they interact to influence the adoption of TSL A
conceptual framework based on the Gestalts approach is developed and tested with a sample of students
from two institutions of learning in Uganda An elaboration about the approach used in this paper is in
the methodological framework Following this is the results and analysis and then discussion of
findings This paper ends with a conclusion
LITERATURE REVIEW
Definition of Technology-Supported Learning
The change from the traditional curriculum to the digital curriculum has revolutionalized higher
education Technology-supported learning has been defined and measured from different perspectives
by researchers Technology-supported learning has been defined by Hardaker and Singh (2011) ldquoas an
innovation situated in the interplay between structure and individual and how this leads to adoption and
diffusionrdquo (p222) Eze et al (2018) have defined TSL as technology-mediated learning that uses
hardware and software systems to enhance the teaching and learning processes Ayele amp Birhanie
(2018) indicate that TSL is a modern way of delivering learning resources to students in higher learning
institutions In this paper we choose to define TSL as e-learning resulting from the interaction between
the organizational and individual factors Gerasimova et al (2018) elaborates that TSL saves studentsrsquo
time and also reduces travel time associated with the traditional face to face approach TSL may
encompass compact disc read-only-memory (CD-ROMs) digital texts podcasts learning management
systems (LMSs) video-technology and websites among others
While CD-ROMs are no longer used widely today Kisanga and Ireson (2015) indicated at that time that
they were a very reliable way of accessing content by students Digital texts and podcasts have been
presented as vital tools for student knowledge delivery in the medical field (Back et al 2019) Learning
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 185
management systems also play a vital role in the delivery of academic resources to students in
universities (Gwamba et al 2018) Bond et al (2018) indicate that LMSs are commonly used among
students in higher education institutions in Germany Nevertheless a recent study by Kim et al (2019)
indicated that students had no experience with LMSs and video technology Chopra et al (2019)
indicate that students are satisfied with web-based learning
Organizational Factors and Technology-Supported Learning
Organizational factors such as management support user training and financial incentives increase the
adoption of TSL ISs in organizations (Ayele amp Birhanie 2018) Shah and Cheng (2019) argue that
development of TSL policies is an opportunity of revolutionizing universities while engaging students
Back et al (2019) suggest that students should practice with ICTs A study by The and Usagawa (2018)
revealed that if a person practices with ICTs they gain confidence in using such tools Shah and Cheng
(2019) similarly indicate that distance learners are faced with many challenges which may force them to
drop out of universities The students cited juggling work and study caring for children financial
difficulty and academic writing among others as challenges to TSL
Another area of concern raised by Shah and Cheng (2019) was the time spent by a student studying off-
campus Such time involves experimenting with ICTs Furthermore they argue that indicators such as
online learning resources relevant course materials and building student confidence are key to positive
learning Students perceive that commitment of university management in uploading the online
resources subscribing to relevant courses and ensuring that the lecturers build confidence in them
contributes to the adoption of TSL
Students perceived that organizational support plays a vital role in their adoption of TSL (Selim 2007)
A study by Bhardwaj and Goundar (2018) reveals that students perceive that university management
does not support their use of TSL We choose to look at the goal of the TSL policy time to experiment
with ICT financial support and commitment of university management as organizational factors that
can influence studentsrsquo adoption of TSL Additionally Moakofhi et al (2017) argue that studying
organizational factors is essential in understanding technological adoption
Individual Factors and Technology-Supported Learning
Individual factors can be termed as personal factors depending on the author The individual in question
is a student Kimiloglu et al (2017) specify that individual factors can explain the adoption of TSL ISs
Parlakkılıccedil (2014) indicated that age influences the use of information technologies In addition Pereira
et al (2018) uphold that people tend to adopt TSL at an early age Gerasimova et al (2018) specified
that the average age of students who adopted TSL at the Russian University of Economics was 23 years
They revealed that the majority of these students appreciated TSL Another study by Bhardwaj and
Goundar (2018) about studentsrsquo perceptions of TSL shows that the majority of the students engaged in
the study were aged between 21 to 30 years of age
With reference to gender female students showed a preference for humanities and social sciences while
their male counterparts preferred engineering natural science and ICT (Zuvic-Butorac et al 2011)
Nevertheless Kim et al (2019) report that female students are more experienced with TSL than males
Additionally Rhema and Miliszewska (2014) revealed that there is no difference between female and
male students when it comes to the acceptance of TSL in Libyan universities Furthermore Ramiacuterez-
Correa et al (2015) studied gender behavior in relation to the studentsrsquo acceptance of TSL in Chile and
Spain Their findings revealed that there is an insignificant difference between male and female students
in the use of TSL
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 186
The year of study of a student is perceived as the level of education in this paper As per the level of
education Damanpour and Schneider (2006) revealed that education level contributes to the adoption of
innovations Technology-supported learning is perceived as something new hence an innovation
Whereas many studies have been carried out on age and gender few studies seem to focus on the
contribution of level of education to the adoption of technological innovations and less so in developing
economies
It should be noted that the definition of TSL in this paper considers the interaction between
organizational and individual factors This implies that organizational factors impact the individual
factors in relation to the adoption of TSL and vice versa
Interaction between Factors of Adoption of Technology-Supported Learning and Their Impact on Technology Supported Learning
Scholars often wonder whether the individual (student) should adapt to the organization or whether the
organization (eg university) should adapt to the individual (Lippman 2013) Lippman observes that
debatably the preceding statements are incorrect It is better to ask ldquoHow do organizations shape the
individualrdquo In turn ldquoHow does the individual impact organizationsrdquo In his argument the university
can be composed of the students other individuals and the formal physical environment Singh et al
(2005) argue that the structure of organizations has changed They indicate that TSL is part and parcel of
the organization Organizational characteristics can impact on a studentsrsquo ability to adopt TSL
Universities are usually expected to provide policies time for interaction financial support and
commitment to the students in relation to the adoption of TSL (Shah amp Cheng 2019 The amp Usagawa
2018) Students have to be in harmony with the university mission in order for the university to achieve
organizational success University TSL policy gives structure to how students should learn assess and
improve their TSL skills in a university (Makerere University Council personal communication
January nd 2004) Maina and Njuki (2015) argue that organizational TSL policies influence the
adoption of TSL The Makerere University Council (personal communication September nd 2015)
highlights that TSL policies boost pedagogical practices and improve end user skills If students are
familiar with university TSL policies chances are high that their intention innovativeness and
acceptance of TSL will be high
The time students take in interacting with ICT is an important issue in learning environments (Salinas
2004) Drent and Meelissen (2008) argued that time can be assessed according to experimenting
interacting and reflecting with ICT Time has an impact on the adoption of TSL (Shah amp Cheng 2019)
among students Developing economies have been reported to have limited e-resources which reduces
individual ability to experiment with such resources The more students experiment with ICT the more
their intention to use innovativeness and acceptance of TSL
Universities are expected to assist students through financial support to boost their adoption of TSL
(Angolia amp Pagliari 2016) They indicate that TSL comes with new support requirements Additionally
they assert that financial support enhances adoption of TSL among students in higher education
institutions They highlight that in cases where institutions often purchase TSL facilities for the students
the TSL adoption rates tend to be high
University management should be committed to supporting students to boost their adoption of TSL
(Bhardwaj amp Goundar 2018) This can be achieved through training students on how to use TSL
facilities (Kim et al 2019) Students perceive that institutional support is one of the enablers for their
adoption of TSL (Okai-Ugbaje 2020)
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 187
According to Lippman (2013) studentsrsquo age gender and level of education influence their organizations
This can be observed through variations in the use of TSL policies in place time one takes interacting
with ICTs making use of resources and also participating in activities within an organization Literature
indicates that TSL policies are common within learning institutions (Drent amp Meelissen 2008) Students
can get acquainted with these policies take time to practise with ICT use acquired TSL facilities in the
university and avail themselves to receive information from university management about TSL
Whenever a new technology is adopted it finds a society with inequalities in terms of age gender and
level of education Thus understanding the impact of age gender and level of education in the adoption
of TSL in organizations is paramount Maina and Nzuki (2015) indicate that age is an important factor in
understanding adoption of innovations in learning organizations Pereira et al (2018) indicate that
adoption of technological innovations usually takes place at an early age Adewole-Odeshi (2014)
amplifies that older people tend to have low interaction with the learning organizations resulting in low
adoption of technological innovations in such organizations
The relationship between gender and different environments has been testified (Lee amp Pituch 2002
Martin 1991) Lee and Pituch (2002) suggested that gender should not be left out in information
technology (IT ) adoption models An early study by Martin (1991) on gender differences in technology
adoption and telephone use found that womenrsquos use of the telephone for socialization purposes helped
to expand its use in both residential and business areas Odewumi et al (2018) indicate that females are
disadvantaged when it comes to the adoption of information technology
Damanpour and Schneider (2006) reveal that education level is an individual factor They continue to
argue that education is an important aspect of the adoption of innovations Maina and Nzuki (2015)
agree that level of education impacts on the learning organization during the adoption of innovations In
some instances education is viewed as a management strategy that can ease implementation of specific
innovations in particular organizations (Ferreira et al 2015) There seems to be little research on how
the level of education impacts on the learning organization during the adoption of innovations this study
acted as a basis to fill the gap A first-year student may have no knowledge of the TSL policy in a
particular learning institution which may affect their use of TSL facilities
Theoretical Underpinnings of the Study
The interactions between organizational and individual factors have been presented indicating the
complexities involved These interactions were studied with different theoretical underpinnings Factors
can be studied from a theoretical point of view that seeks to predict TSL from both organizational
(macro) and individual (micro) perspectives (Hardaker amp Singh 2011) Sometimes referred to as the
ldquoduality of structurerdquo factors can be drawn from the works of Giddens lsquotheory of structurationrsquo who
argues that macro and micro perspectives are interlinked Giddens theory is mapped to that of (Rogers
2003)rsquos Diffusion of Innovations Theory to ensure that the factors of adoption of TSL are objectively
measured For instance individual (student) was operationalized according to factors of age gender and
level of education The concept of adoption of TSL has been operationalized as intention to use
innovative use and acceptance of TSL Students can perceive that the factors encourage the adoption of
TSL or not The factors that predict successful adoption of TSL have been studied by using the
conceptual framework in Figure 1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 188
Figure 1
The Conceptual Framework of Predictors of Successful Adoption of Technology- Supported
Learning (TSL) in Universities in Uganda
Gestalts Perspective in this Study
To represent the complex interactions we have incorporated Venkatraman (1989)rsquos Gestalts fit which is
an alignment perspective Venkatraman indicates that alignment aims at balancing related organizational
components This is usually done with the aim of achieving organizational success Gestalts fit has been
achieved by configuring factors that are unique tightly integrated and fairly stable We argue that
measuring organizational and individual factors using a linear model is not appropriate Thus alignment
as Gestalts was adopted to identify those configurations of organizational and individual factors that
predict the adoption of TSL in universities
If configurational factors of the framework (ie organizational and individual factors) are well aligned
then there is greater interaction and thus an increase in the adoption of TSL On the other hand if the
elements are misaligned the level of adoption of TSL is low Thus the following hypotheses were tested
by the researchers The greater the alignment between the organizational and individual factors the more
the i) intention to use ii) innovative use and iii) acceptance of TSL in universities will be
Table 1 provides the definitions of these factors In the conceptual framework the third element is an
outcome of the interaction or interplay between the first and second variables
Table 1
Factors Constructs Employed in the Study
Factors Constructs Operationalization References
Organization Goal of TSL policy availability of time
to experiment with ICT availability of
financial support and commitment of
management
Rogers 2003 Shah amp Cheng
(2019)
Individual (student) Student age gender and level of
education
Glazier et al (2019)
Alignment
Between 1 amp 2
Organization (1) Individual
(2)
Adoption of TSL
in universities in
Uganda (3)
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 189
Factors Constructs Operationalization References
Interaction The interaction between the main factors
ie organization and the individual
affect each other
Drazine amp Van de Ven (1985)
Perception This is the studentrsquos perspective that
indicates whether the factors encourage
adoption or not
Gerasimova et al (2018)
Alignment Level of coherence Venkatraman (1989)
Adoption of TSL Intention to use innovative use and
acceptance of TSL
Rogers (2003) Davis (1989)
METHODOLOGICAL FRAMEWORK
To investigate the predictors of the successful adoption of TSL among students the quantitative survey
mixed and cross-sectional research designs were used (Creswell 2014 Greene et al 1989) A recent
study by Shah and Cheng (2019) carried out on studentsrsquo perceptions used a quantitative research
design Thus the same design was adopted for this study In quantitative designs surveys are usually
used The researchers used a survey to collect data from a total of 184 students The survey was
structured into four main parts background information adoption of TSL organizational and individual
factors Bhardwaj and Goundar (2018) in their study on studentsrsquo perceptions on TSL used a mixed
research approach The researchers adopted the said research approach whereby the largely quantitative
and little qualitative techniques were used
Besides lecturers the population of study included students from both Makerere and Gulu universities
Students were chosen because they are the main users of TSL (Bhardwaj amp Goundar 2018) and they are
faced with challenges in using this type of learning (Gerasimova et al 2018) Purposive and simple
random sampling were used for quantitative data The given universities were purposively chosen
because of the level of knowledge and use of TSL Simple random sampling was used at departmental
level to collect quantitative data from students of agricultural sciences because they are among the main
users of TSL facilities at this level Purposive homogeneous sampling was used for qualitative data A
total of six students were interviewed to complement the questionnaire data
The study took place at a particular point in time hence it was cross-sectional in nature Internal and
external validity checks were used (Bhattacherjee 2012) Internal validity was achieved by omitting
extraneous variables so that changes in the response to variables is caused by the hypothesized
explanatory variables External validity was achieved by generalizing from Makerere and Gulu
universities to other universities These two universities were chosen because their lecturers have been
motivated earlier their students would have had more exposure to the technology adoption and with that
experience it would be appropriate to capture their perspectives Validity of the student qualitative
instrument was achieved through use of research experts who were used to validate whether the content
in the instrument could get the data required (Ozkan amp Koseler 2009)
Additionally the developed question concepts were derived from past relevant studies This can be
related to Bhardwaj and Goundar (2019) who captured studentsrsquo perceptions on TSL based on the
modification of concepts from relevant past studies Studies on studentsrsquo perceptions taking a
quantitative approach are usually carried out using reliability tests Kim et al (2019) carried out a
reliability test on a questionnaire that was administered to undergraduate students in a university in
Korea using Cronbachrsquos alpha Similarly the researchers used the same alpha to test questions in the
student self-administered questionnaire The outcome variable of the adoption of TSL was
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 190
operationalized as intention to use innovative use and acceptance of TSL with Cronbach alphas of 064
067 070 respectively The organizational factors had a Cronbach alpha of 073 The researchers
followed ethics guidelines to accomplish the study
RESULTS AND ANALYSIS
Background Information
The majority (821) of the students were aged between 21 and 30 years old This is in line with
Bhardwaj and Goundar (2018) who indicated that the majority of the student respondents were between
21 to 30 years old The majority (641) of the student respondents were male while 359 were female
respondents This is in line with Zuvic-Butorac et al (2011) who found that female students
concentrated on art subjects while their male counterparts were in engineering natural science and ICT
Most (410) of the students were in their second year of study followed by first year students (ie
320) The majority of the students (ie 940) had access to email Few (386) students had laptops
This is because these students may not be in position to afford such devices Most (592) of the
respondents revealed that there are functional TSL laboratories in their universities Most of the students
(571) were affiliated to Gulu University For descriptive analysis of means and standard deviations
for selected research variables see Tables 2 and 3 All the data simulations were based on a Likert scale
of 5 Descriptive analysis of the individual (student) presenting modal age gender and level of education
of the whole population of students (ie N =184) is shown in Table 3
Descriptive Statistics
Table 2
Descriptive Statistics for Selected Research Variables (N =184)
Variable Brief Description of Variables M a Min Max SD
Adoption of TSL
Intention to Use
ITU1 Computers 445 1 5 0979
ITU2 CD-ROMs 283 1 5 1468
ITU3 Web-based learning 384 1 5 1344
ITU4 Video conferencing 359 1 5 1449
ITU5 University TSL environments eg Black-Board 366 1 5 1425
Innovative Use
INU1 I am able to expound on what lecturers have provided to me in class using
the Internet
379 1 5 1334
INU2 I am able to make presentations in text audio and visual 380 1 5 1424
INU3 I am able to communicate with other students through online discussions
emails wikis and WhatsApp
371 1 5 1496
Acceptance
ACC1 Computers 452 1 5 0941
ACC2 CD-ROMs 296 1 5 1536
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 191
Variable Brief Description of Variables M a Min Max SD
ACC3 Web-based learning 375 1 5 1388
ACC4 Video conferencing 359 1 5 1376
ACC5 University TSL environments eg Black-Board 361 1 5 1536
Organizational Factors
GUELP1 Goal of university TSL policy 297 1 5 1408
ATIEXICT1 Availability of time to experiment with ICT 322 1 5 1366
AFS1 Availability of financial support 273 1 5 1544
COMAN1 Commitment of management 304 1 5 1362
a A score of 350 indicates that the person has and there was ldquoeg intention to use TSL encouragement
on use of TSL facilities and ldquohindrance to the progress of TSL ISsrdquo on the five-point Likert scale of
1(Very little or no intention to use TSL encouragement on use of TSL facilities and hindrance to the
progress of TSL ISs ) and 5(Very much intention to use TSL greatest encouragement on use of TSL
facilities and very much hindrance to the progress of TSL ISs)
Students had lsquomuchrsquo intention to use TSL facilities For instance they had lsquomuchrsquo intention to use
computers (ITU1) The students had lsquomuchrsquo innovative use of TSL (for instance they were able to make
presentations in text audio and video INU2) They also indicated very much acceptance of TSL For
instance they had very much acceptance of computers (ACC1)
See Table 3 for most frequent characteristics of each individual in the whole student population (ie N
=184)
Table 3
Individual Factors (N = 184)
Individual Factors Rate of Occurrence Most Frequent
Individual Factors
AGE Most frequent age of students 25 Years
GEN Most frequent gender of students Male
LEDUC Most frequent year of study of students Year 2
Cluster Analyses
The researchers used the k-means clustering algorithm with the help of Statistica Software version 133
to generate six clusters The data were standardized Whereas several simulations were carried out (ie1
2 3 4 5 and 6) only the sixth simulation showed acceptable results All 6 simulations yielded p values
less than 005 (see Table 4) Table 4 indicates the measurement of the organizational factors and
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 192
adoption of TSL in universities in Uganda across the six student clusters Table 5 shows the
measurement of the individual factors across the said clusters
Table 4
Cluster Analysis and Analysis of Variance for Students
Cluster
Variable 1
(n = 37)
2
(n = 38)
3
(n = 19)
4
(n = 42)
5
(n = 24)
6
(n = 24)
ANOVA
F p
Adoption of TSL
Intention to Use TSL
ITU1 011 024 002 032 048 -161 244 00
ITU2 -007 -074 033 069 -014 -005 1109 00
ITU3 -101 037 035 058 039 -072 2502 00
ITU4 -084 031 031 059 031 -079 1893 00
ITU5 -056 022 -006 059 029 -078 1159 00
Innovative Use of TSL
INU1 -025 051 -024 065 -013 -122 2075 00
INU2 014 029 -142 049 052 -092 2671 00
INU3 -051 044 -128 061 049 -045 2449 00
Acceptance of TSL
ACC1 023 023 007 039 034 -179 3439 00
ACC2 -021 -085 050 092 018 -052 2579 00
ACC3 -087 041 007 064 033 -081 2219 00
ACC4 -100 027 029 067 057 -086 3169 00
ACC5 -065 001 -013 064 066 -069 1529 00
Organizational Factors
GUELP1 004 032 -024 078 -099 -075 2078 00
ATIEXICT1 019 -051 -069 089 -009 -040 1636 00
AFS1 012 -051 -044 105 -053 -036 2228 00
COMAN1 001 -017 -057 074 -018 -039 835 00
Note Positive values are indicated in bold while negative ones are not in bold
Table 5
Individual Factors per Cluster
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
AGE Most frequent
age of
students
26
Years
25
Years
25
Years
25
Years
26
Years
24
Years
356 00
GEN Most frequent
gender of
students
Male Equal
number
of male
and
female
Female Male Male Male 426 00
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 193
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
LEDUC Most frequent
year of
study of
students
Year 2 Year 2 Year 1 Year 2 Year 4 Year 1 409 00
Qualitative Analysis
Thematic analysis was used in analyzing qualitative data We used Braun and Clarke (2006)rsquos six
thematic analysis steps of familiarization generating initial codes searching reviewing defining and
naming themes and producing a report Studentsrsquo data comprised student interview data items from
which initial extracts were made Familiarization was carried out by reading and re-reading the said data
items Generating initial codes was achieved through capturing features of interest from the student data
set Searching was achieved through grouping student data relevant to potential themes Defining and
naming was achieved by categorizing the themes Finally a report about the student data was produced
The researchers used the most significant interview data that could support the quantitative results
presented in this paper in the discussion of findings section Thus the discussion of findings is
integrative
DISCUSSION OF FINDINGS
In this section qualitative findings have been integrated with the quantitative ones The letter lsquoSrsquo
denotes student Cluster 1 students were ranked third as far as the adoption of TSL is concerned because
of the quite weak alignment between the configurational factors For instance the students had no
intention to use web-based technology This was confirmed by student S5 who revealed that she did not
understand web-based learning These students could not interact with their colleagues using TSL
facilities Students in this cluster never embraced video conferencing technology because it is limited as
reflected in the main themes by the students S1 S3 and S5 However these students had the intention to
use computer technology This is consistent with student S1 who commented that ldquoI have the intention
to use computers for academic purposesrdquo They also had innovative use of TSL shown through their
ability to incorporate text audio and visual technology Furthermore these students accepted computer
technology This is supported by students S1 S2 and S6 who revealed that they use computers because
of the current education trend which demands them to be computer literate for academic purposes and
they are easy to work with
Further analysis of this cluster indicates that the organizational factors encourage these students to use
TSL facilities (see Table 4) Qualitative results from students S1 S4 and S3 respectively had the
following implications on the organizational factors
bull the goal of the TSL learning policy encourages the use of TSL facilities at a minimal level
bull students practise with ICT and also believe that the university indirectly supports them financially by
providing limited wireless fidelity
bull the university management is supportive by designing sessions on how to use computers
A typical student in this cluster was 26 years old male by gender and in his second year of study (see
Table 5) While these students have similar characteristics with those of Cluster 6 they have tried to
adopt TSL facilities compared Cluster 6 students because of their experience with such facilities
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 194
Cluster 2 students ranked second as far as adoption of TSL is concerned For example students in this
cluster revealed lsquomuchrsquo intention to use TSL For instance student S1 confirmed that ldquoWeb-based
learning offers more informationrdquo Students in this cluster were lsquovery muchrsquo capable of expounding on
what lecturers had provided to them in class using the Internet This was through ldquosurfingrdquo the Internet
using the Google search engine as revealed by student S1 Students in this cluster had lsquomuchrsquo
acceptance of TSL facilities such as web-based facilities This is because web-based learning can be
used for research work and expounding on what is taught in class by lecturers as revealed by student S1
This is confirmed by a recent study by Chopra et al (2019) that indicates that students are satisfied by
web-based technology
In relation to the organizational factors students in Cluster 2 agreed that the goal of university TSL
policy encourages their use of TSL facilities The qualitative results suggest that e-discussions can
compel students to use TSL facilities as revealed by Student S3 On average students in this cluster
were aged 25 years the number of male students was equivalent to that of female ones and they were in
their second year of study (see Table 5) These students could be better adopters than those of Cluster 1
because they seemed to have an equal gender distribution Such distribution may account for an unequal
educational technology use among Cluster 1 and 2 students who enjoyed a similar learning experience
(see Tables 4 and 5) Students of this cluster seemed to be better adopters than those of Clusters 1 3 5
and 6 because of their ability to make use of the TSL policy to their advantage (see Tables 4 and 5)
Cluster 3 students were low adopters of TSL because of low alignment between the configurational
factors thus ranked fifth as far as adoption of TSL is concerned These students lacked innovative use of
TSL facilities implying that these students cannot use such facilities to improve their learning
capabilities The same students however registered lsquovery muchrsquo acceptance of CD-ROMs (see Table 4)
This could be because this medium is a dependable way of accessing content by students (Kisanga amp
Ireson 2015)
Students in Cluster 3 perceived that the organizational factors never contributed to their use of TSL
facilities in any way (see Table 4) For example students had no time to experiment with ICT This
could be because students never practise with ICT due to the fact that the course is ldquohecticrdquo and the IT
laboratories are usually closed over the weekend as revealed by student S1 The average age gender
and level of education of a student in this cluster is 25 years female and first-year respectively (see
Table 5) These could be lower adopters of TSL than members of Clusters 2 and 5 because of their
gender Female respondents are disadvantaged when it comes to the use of information technology
(Odewumi 2018) Another plausible reason for the low adoption levels in Cluster 3 compared to those
in Clusters 2 and 1 could be the lack of innovative use of TSL (see Table 4)
Cluster 4 students were the greatest adopters of TSL among the six clusters This is because they had the
lsquogreatestrsquo alignment between the configurational factors These students are eager to use ICT innovative
and embraced TSL They are eager to use CD-ROM technology because such technology is cheap and
stores information as confirmed by students S1 and S6 They can innovatively expound on what
lectures have provided to them in class using the Internet with the help of search engines (such as
Google) as indicated by student S1 They have embraced video conference technology Students S1 S3
and S5 confirmed that they were able to imitate the limited video conferencing learning using the
WhatsApp facility
Students in Cluster 4 perceived that the organizational factors encouraged their use of TSL facilities
High scores were registered on the goal of the university TSL policy time to experiment with ICT
financial support and commitment of university management For instance during the interview process
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 195
student S3 revealed that ldquoa discussion policy for example may improve adoption of [TSL] because
once e-discussions are made they can compel one to use the [TSL] facilitiesrdquo The result from the
interview process on time to experiment with TSL conflicts with the cluster one whereby the majority
of the students never found time to practise with TSL facilities Shah and Cheng (2019) however
indicate that time influences the adoption of TSL facilities Quantitative findings in this cluster on
financial support could be related to those of student S3 who indicated that there was indirect financial
support by their university through the provision of wireless technology On the issue of management
commitment findings are in line with those of student S4 who felt that university management was
committed because they designed computer literacy sessions for them A typical student in this cluster
was 25 years old male by gender and in year 2 of study (see Table 5) This cluster (n = 42) had the
majority of the student respondents among the six clusters
The alignment of the configurational factors in Cluster 5 seemed to be lsquoweakerrsquo than that of Cluster 1
thus this cluster was ranked fourth Whereas the students in this cluster indicated lsquovery muchrsquo adoption
of TSL in some instances the configurational variables registered low scores For instance they had
very much acceptance of TSL environments yet they seemed not to be familiar with the TSL policy
The result on acceptance of TSL environments is parallel to that of Bond et al (2018) who indicated that
such environments are commonly used by students in higher education institutions in Germany The
result on the TSL policy was confirmed by student S4 who revealed that the TSL policy is not
effectively implemented in the university A normal student in this cluster was 26 years old male by
gender and in year 4 of the study (see Table 5) These students could be better adopters of TSL than
those of Clusters 3 and 6 because of their long-time experience with TSL as reflected in their year of
study compared to the said clusters (see Tables 4 and 5) It is not surprising this cluster had the best
distributions of ICTs among students
Similar to Cluster 5 Cluster 6 had 24 respondents (see Table 4) However students in this cluster are
coincidentally ranked as non-adopters of TSL among the six clusters (see Tables 4 and 5) This is
because there is no alignment between the configurational factors resulting in no adoption of TSL
These students were not willing to use IT could not modify their learning capabilities using IT and had
not realised the value of IT tools All 24 respondents in this cluster lsquoconcurredrsquo that the organization
never encouraged their use of TSL facilities This could imply that students were not involved at all
during the adoption of TSL Shah and Cheng (2019) reveal that students perceive that juggling work and
study caring for children financial difficulty and academic writing among other factors affect their
ability to adopt TSL On average students in this cluster were 26 years old male by gender and in year
1 of their study Being in their first year of study could imply that they had little experience with TSL
CONCLUSION
Identification of predictors of successful adoption of TSL among students was achieved using the
Gestalts approach Students perceived that organizational and individual factors predict successful
adoption of TSL Cluster 4 is the most coherent and as such adopted TSL most This is because the
organizational and individual factors were most aligned For example when students in this cluster are
financially supported and are in their second year of study they are eager to use to be innovative with
and embrace TSL And because of their eagerness innovativeness and ability to embrace TSL they have
accumulated more experience than others Cluster 6 students are non-adopters because they are more
inexperienced with TSL than the rest of the students
There seems to be a gap in the use of the non-linear techniques (eg clustering technique) in studies on
studentsrsquo perceptions Most studies for instance Chopra et al (2019) Gerasimova et al (2018) and Shah
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 196
and Cheng (2019) who have measured student perceptions have used linear techniques Thus this study
has closed this gap This study is a benchmark for universities in developing economies to integrate TSL
at university level For instance it should be noted that in order to achieve successful adoption of TSL
among students in universities management must be involved Nabushawo et al (2018) suggest that the
commitment of management can be achieved by collaborating with and training the users of TSL ISs
Since the world is challenged by Corona Virus Disease (COVID) this study can be used as model to
avail learning materials to students without spreading this disease
It should be noted that the rate of adoption of TSL among students is still low yet they have advanced in
age This contradicts Pereira et al (2018) who indicated that adoption of TSL usually takes place at an
early age It is therefore recommended that students should be supported to adopt TSL during their
earlier career years so that universities in Uganda can benefit from this innovation This can be done by
introducing TSL at primary level Universities need to strengthen their management capabilities such as
increasing the time studentsrsquo have to experiment with ICTs Further research is required to develop
strategies that can be adopted to enhance adoption of TSL among students at earlier ages Although this
study was carried out at a particular point in time it can also be carried out longitudinally There are
many indicators of the organization individual (student) and adoption of TSL besides those presented in
the conceptual framework Further research can be carried out on those Besides organization and
individual factors there is need to know the role of other factors in the adoption of TSL among students
While students from only two public universities were considered for this study students from other
universities can be considered as well
ACKNOWLEDGMENTS
The researchers want to thank the Almighty God for the gift of knowledge wisdom and understanding
in the writing of this paper The researchers also thank the Organization for Women in Science for the
Developing World (OWSD) and the Swedish International Development Agency (SIDA) for their
financial support in carrying out the study
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Acosta M L Sisley A Ross J Brailsford I Bhargava A Jacobs R amp Anstice N (2018) Student acceptance of e-
learning methods in the laboratory class in optometry PLOS ONE 13(12) 1-15
httpsdoiorg101371journalpone0209004
Adewole-Odeshi E (2014) Attitude of students towards e-learning in South-West Nigerian universities An application of
technology acceptance model Library Philosophy and Practice Article 1035
Angolia M G amp Pagliari L R (2016) Factors for successful evolution and sustainability of quality distance education
Online Journal of Distance Learning Administration 19(3)
Ayele B A amp Birhanie W K (2018) Acceptance and use of e-learning systems The case of teachers in technology
institutes of Ethiopian universities Applied Informatics 5(1) 1-11 httpsdoiorg101186s40535-018-0048-7
Back D A von Malotky J Sostmann K Peters H Hube R amp Hoff E (2019) Experiences with using e-learning tools
in orthopedics in an uncontrolled field study application Orthopaedics amp Traumatology Surgery amp Research
105(2) 389-393 httpsdoiorg101016jotsr201901002
Bhardwaj A amp Goundar S (2018) Students perspective of elearning and the future of education with MOOCs
International Journal of Computer Engineering 7(5) 248-260
Bhattacherjee A (2012) Social science research Principles methods and practices Textbooks Collection
httpscholarcommonsusfeduoa_textbooks3
Bond M Mariacuten V I Dolch C Bedenlier S amp Zawacki-Ritcher O (2018) Digital transformation in German higher
education Student and teacher perceptions and usage of digital media International Journal of Educational
Technology in Higher Education 15(48) httpsdoiorg101186s41239-018-0130-1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 197
Braun V amp Clarke V (2006) Using thematic analysis in psychology Qualitative Research in Psychology 33 77-101
Chopra G Madan P Jaisingh P amp Bhaskar P (2019) Effectiveness of e-learning portal from studentsrsquo perspective A
structural equation model (SEM) approach Interactive Technology and Smart Education 16(2) 94-116
httpsdoiorg101108ITSE-05-2018-0027
Creswell J W (2014) Research Design Qualitative quantitative and mixed methods approaches (4th ed) Sage
Publications
Damanpour F amp Schneider M (2006) Phases of the adoption of innovation in organisations Effects of environment
organisation and top managers British Journal of Management 17 215ndash236 httpsdoiorg101111j1467-
8551200600498x
Davis F D (1989) Perceived usefulness perceived ease of use and user acceptance of information technology MIS
Quarterly 13(3) 319ndash340 httpsdoiorg102307249008
Drazin R amp Van de Ven A H (1985) Alternative forms of fit in contingency theory Administrative Science Quarterly
30(4) 514-539 httpsdoiorg1023072392695
Drent M amp Meelissen M (2008) Which factors obstruct or stimulate teacher educators to use ICT innovatively
Computers amp Education 51 187ndash199 httpsdoiorg101016jcompedu200705001
Eze S C Chinedu-Eze V C amp Bello A O (2018) The utilisation of e-learning facilities in the educational delivery
system of Nigeria A study of M-University International Journal of Educational Technology in Higher Education
15 (34) 1-20 httpsdoiorg101186s41239-018-0116-z
Ferreira A Teixeira A L amp Dantas A R (2015) Non-technological innovation activities mediate the impacts of the
intra- and extra-organisational contexts on technological innovation outputs Enterprise and Work Innovation
Studies 11 9-43
Gerasimova V G Melamud M R Tutaeva D R Romanova Y D amp Zhenova N A (2018) The adoption of e-learning
technology at the Faculty of Distance Learning of Plekhanov Russian University of Economics Journal of Social
Studies Education Research 9(2) 172-188
Glazier R A Hamann K Pollock P H amp B Wilson B M (2019) Age gender and student success Mixing face-to-face
and online courses in political science Journal of Political Science Education 16(2) 142-157 httpsdoiorg1010801551216920181515636
Greene J C Caracelli V J amp Graham W F (1989) Toward a conceptual framework for mixed method evaluation
designs Educational Evaluation and Policy Analysis 11(3) 255-274 httpsdoiorg1023071163620
Gwamba G Renken J Nampijja J Mayende G amp Muyinda P B (2018) Contextualisation of e-learning systems in
higher education institutions In M Auer amp T Tsiatsos (Eds) Interactive mobile communication technologies and
learning Proceedings of the 11th IMCL conference (pp 44-55) Springer
Hardaker G amp Singh G (2011) The adoption and diffusion of eLearning in UK universities A comparative case study
using Giddenss theory of structuration Campus-Wide Information Systems 28(4) 221ndash233
httpsdoiorg10110810650741111162707
Kim H J Hong A J amp Song H (2019) The roles of academic engagement and digital readiness in studentsrsquo
achievements in university e-learning environments International Journal of Educational Technology in Higher
Education 16(21) 1-18 httpsdoiorg101186s41239-019-0152-3
Kimiloglu H Ozturan M amp Kutlu B (2017) Perceptions about and attitude toward the usage of e-learning in corporate
training Computers in Human Behavior 72 339-349 httpsdoiorg101016jchb201702062
Kisanga D amp Ireson G (2015) Barriers and strategies on adoption of e-learning in Tanzanian higher learning institutions
Lessons for adopters International Journal of Education and Development using Information and Communication
Technology (IJEDICT) 11(2) 126-137
Lee Y-K amp Pituch K (2002 December 10ndash13) Moderators in the adoption of e-learning An investigation of the role of
gender [Article] The Second International Conference on Electronic Business Taipei Taiwan
Lippman P C (2010) Can the physical environment have an impact on the learning environment CELE Exchange
httpsdoiorg1017875km4g21wpwr1-en
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 198
Maina M K amp Nzuki D M (2015) Adoption determinants of e-learning management system in institutions of higher
learning in Kenya A case of selected universities in Nairobi metropolitan International Journal of Business and
Social Science 6(2) 233ndash248
Martin M (1991) The culture of the telephone In PD Hopkins (Ed) Sexmachine Readings in culture gender and
technology (pp 50-74) Indiana University Press
Moakofhi M Leteane O Phiri T Pholele T amp Sebalatlheng P (2017) Challenges of introducing e-learning at
Botswana University of Agriculture and Natural Resources Lecturersrsquo perspective International Journal of
Education and Development using ICT 13( 2) 4-20
Nabushawo H M Muyinda P B Isabwe G M N Prinz A amp Mayende G (2018) Improving online interaction among
blended distance learners at Makerere University In M E Auer D Guralnick amp I Simonics (Eds) Advances in
Intelligent Systems and Computing (pp 63-69) Springer httpsdoiorg101007978-3-319-73210-7_8
Odewumi M O Yusuf M O amp Oputa G O (2018) UTAUT model Intention to use social media for learning interactive
effect of postgraduate gender in South-West Nigeria International Journal of Education and Development using
Information and Communication Technology (IJEDICT) 14(3) 239-251
Okai-Ugbaje S Ardzejewska K amp Imran A (2020) Readiness roles and responsibilities of stakeholders for sustainable
mobile learning adoption in higher education Education Sciences 10(3) 49-69
httpsdoiorg103390educsci10030049
Ozkan S amp Koseler R (2009) Multi-dimensional studentsrsquo evaluation of e-learning systems in the higher education
context An empirical investigation Computers amp Education 53(4) 1285ndash1296
httpsdoiorg101016jcompedu200906011
Parlakkılıccedil A (2014) Change management in transition to e-learning system Qualitative and Quantitative Methods in
Libraries 3(3) 637ndash651
Pereira A Martins P Morgado L amp Fonseca B (2018) Technological proposal using virtual worlds to support
entrepreneurship education for primary school children In M E Auer D Guralnick amp I Simonics (Eds)
Advances in Intelligent Systems and Computing (pp 124-132) Springer
Ramiacuterez-Correa P E Arenas-Gaitaacuten J amp Rondaacuten-Cataluntildea F J (2015) Gender and acceptance of e-learning A multi-
group analysis based on a structural equation model among college students in Chile and Spain PLOS ONE
10(10) 1-17 httpsdoiorg101371journalpone0140460
Rhema A amp Miliszewska I (2014) Analysis of student attitudes towards e-learning The case of engineering students in
Libya Issues in Informing Science and Information Technology 11 169-190 httpsdoiorg10289451987
Rogers E M (2003) Diffusion of innovations (5th ed) Free Press
Salinas J (2004) Cambios metodoloacutegicos con las TIC Estrategias didaacutecticas y entornos virtuales de ensentildeanza-aprendizaje
Bordoacuten 56(3-4) 469-481
Selim H M (2007) Critical success factors for e-learning acceptance Confirmatory factor models Computers amp
Education 49(2) 396ndash413 httpsdoi101016jcompedu200509004
Shah M amp Cheng M (2019) Exploring factors impacting student engagement in open access courses Open learning The
Journal of Open Distance and E-Learning 34(2) 187-202 httpsdoiorg1010800268051320181508337
Singh G ODonoghue J amp Worton H (2005) A study into the effects of elearning on higher education Journal of
University Teaching and Learning Practice 2(1) 13-24
Tchamyou V S (2017) The role of knowledge economy in African business Journal of the Knowledge Economy 8(4)
1189ndash1228 httpsdoiorg101007s13132-016-0417-1
The M M amp Usagawa T (2018) A comparative study of studentsrsquo readiness on e-learning education between Indonesia
and Myanmar American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS) 40(1)
113-124
Venkatraman N (1989) The concept of fit in strategy research Toward verbal and statistical correspondence Academy of
Management Review 9(3) 513-525 httpsdoiorg102307258177
Zuvic-Butorac M Nebic Z amp Nemcanin D (2011) Establishing an institutional framework for an e-learning
implementation Experiences from the University of Rijeka Croatia Journal of Information Technology Education
Innovations in Practice 10 43-56 httpsdoiorg10289451364
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Recommended Citation
-
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Cover Page Footnote
-
- tmp1624440487pdfGS9c9
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Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 183
Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
Research Paper
Volume 13 Issue 2 June 2021 ISSN 1936-0282
Esther Namirembe
Makerere University
frixie2002usyahoocom
Michael Kyobe
University of Cape Town
MichaelKyobeuctacza
(Received August 2020 accepted January2021)
ABSTRACT
This study identified the predictors of successful adoption of technology supported learning (TSL)
among students in universities Presumably the perspective of the students in understanding this study is
crucial because students are key users of TSL systems and are faced with challenges in the adoption of
such systems in learning institutions We argue in the present study that predictors can be identified
using Gestalts approach given the complex interactions between the organizational and individual
factors The extent of interaction between the factors was accomplished using the clustering algorithm
Data was collected from 184 students from Makerere and Gulu universities Six clusters emerged out of
the findings of which Cluster 4 students adopted TSL the most These students indicated that successful
adoption of TSL is best achieved when there is coherence between financial support and when they are
in their second year of study
Keywords
Predictors technology supported learning universities Uganda Gestalts approach
INTRODUCTION
Predictors can be regarded as factors In this paper they are regarded as factors required for successful
adoption of technology-supported learning (TSL) These predictors can be categorized as organizational
and individual factors In this paper organizational factors are operationalized as the availability of the
goals of the university TSL policy time to experiment with information and communication technology
(ICT) financial support and commitment of university management With regard to this paper
individual factors are operationalized as age gender and level of education Whereas it has been
established that there are predictors that contribute to successful adoption of TSL there is growing
concern that if such predictors are not investigated adoption of TSL information systems (ISs) may
continue to be a challenge
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 184
Universities in developing economies in particular have adopted technology-supported learning
information systems (TSL ISs) to boost the knowledge society (Tchamyou 2017) Since students are the
key users of TSL (Bhardwaj amp Goundar 2018) in universities understanding their perspective in the
adoption of TSL would be paramount to educational re-engineering In addition students face
challenges during their encounter with TSL (Gerasimova et al 2018) They indicate that such
challenges or factors include lack of self-discipline and motivation financial implications and lack of
face to face interaction with a tutor Given the fact that these factors in adoption of TSL have a great
impact on students it is worth investigating such factors to augment their (studentsrsquo) learning in
universities
Other writers have reported disparities in who uses technology and at what age they are exposed to it In
order to understand the predictors of adoption and effective use of technology in education the
perspective of students regarding the adoption of technology and their views about what the institutions
should provide to make this adoption possible is critical However not many studies have looked at this
problem from the perspective of students who happen to use the TSL (Acosta et al 2018) In the present
study the researchers investigate the predictors of successful adoption of TSL as perceived by students
The Gestalts approach was adopted given the fact that the predictors are complex and interactional
making it difficult to measure their influence Gestalts is defined as configuration of institutional
components that has achieved a satisfactory high level of coherence (Venkatraman 1989) Gestalts
scholars argue that success is only achieved when the components achieve a satisfactorily high level of
coherence
The present study focuses on two categories of predictors organizational and individual factors The
next section reviews these predictors and how they interact to influence the adoption of TSL A
conceptual framework based on the Gestalts approach is developed and tested with a sample of students
from two institutions of learning in Uganda An elaboration about the approach used in this paper is in
the methodological framework Following this is the results and analysis and then discussion of
findings This paper ends with a conclusion
LITERATURE REVIEW
Definition of Technology-Supported Learning
The change from the traditional curriculum to the digital curriculum has revolutionalized higher
education Technology-supported learning has been defined and measured from different perspectives
by researchers Technology-supported learning has been defined by Hardaker and Singh (2011) ldquoas an
innovation situated in the interplay between structure and individual and how this leads to adoption and
diffusionrdquo (p222) Eze et al (2018) have defined TSL as technology-mediated learning that uses
hardware and software systems to enhance the teaching and learning processes Ayele amp Birhanie
(2018) indicate that TSL is a modern way of delivering learning resources to students in higher learning
institutions In this paper we choose to define TSL as e-learning resulting from the interaction between
the organizational and individual factors Gerasimova et al (2018) elaborates that TSL saves studentsrsquo
time and also reduces travel time associated with the traditional face to face approach TSL may
encompass compact disc read-only-memory (CD-ROMs) digital texts podcasts learning management
systems (LMSs) video-technology and websites among others
While CD-ROMs are no longer used widely today Kisanga and Ireson (2015) indicated at that time that
they were a very reliable way of accessing content by students Digital texts and podcasts have been
presented as vital tools for student knowledge delivery in the medical field (Back et al 2019) Learning
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 185
management systems also play a vital role in the delivery of academic resources to students in
universities (Gwamba et al 2018) Bond et al (2018) indicate that LMSs are commonly used among
students in higher education institutions in Germany Nevertheless a recent study by Kim et al (2019)
indicated that students had no experience with LMSs and video technology Chopra et al (2019)
indicate that students are satisfied with web-based learning
Organizational Factors and Technology-Supported Learning
Organizational factors such as management support user training and financial incentives increase the
adoption of TSL ISs in organizations (Ayele amp Birhanie 2018) Shah and Cheng (2019) argue that
development of TSL policies is an opportunity of revolutionizing universities while engaging students
Back et al (2019) suggest that students should practice with ICTs A study by The and Usagawa (2018)
revealed that if a person practices with ICTs they gain confidence in using such tools Shah and Cheng
(2019) similarly indicate that distance learners are faced with many challenges which may force them to
drop out of universities The students cited juggling work and study caring for children financial
difficulty and academic writing among others as challenges to TSL
Another area of concern raised by Shah and Cheng (2019) was the time spent by a student studying off-
campus Such time involves experimenting with ICTs Furthermore they argue that indicators such as
online learning resources relevant course materials and building student confidence are key to positive
learning Students perceive that commitment of university management in uploading the online
resources subscribing to relevant courses and ensuring that the lecturers build confidence in them
contributes to the adoption of TSL
Students perceived that organizational support plays a vital role in their adoption of TSL (Selim 2007)
A study by Bhardwaj and Goundar (2018) reveals that students perceive that university management
does not support their use of TSL We choose to look at the goal of the TSL policy time to experiment
with ICT financial support and commitment of university management as organizational factors that
can influence studentsrsquo adoption of TSL Additionally Moakofhi et al (2017) argue that studying
organizational factors is essential in understanding technological adoption
Individual Factors and Technology-Supported Learning
Individual factors can be termed as personal factors depending on the author The individual in question
is a student Kimiloglu et al (2017) specify that individual factors can explain the adoption of TSL ISs
Parlakkılıccedil (2014) indicated that age influences the use of information technologies In addition Pereira
et al (2018) uphold that people tend to adopt TSL at an early age Gerasimova et al (2018) specified
that the average age of students who adopted TSL at the Russian University of Economics was 23 years
They revealed that the majority of these students appreciated TSL Another study by Bhardwaj and
Goundar (2018) about studentsrsquo perceptions of TSL shows that the majority of the students engaged in
the study were aged between 21 to 30 years of age
With reference to gender female students showed a preference for humanities and social sciences while
their male counterparts preferred engineering natural science and ICT (Zuvic-Butorac et al 2011)
Nevertheless Kim et al (2019) report that female students are more experienced with TSL than males
Additionally Rhema and Miliszewska (2014) revealed that there is no difference between female and
male students when it comes to the acceptance of TSL in Libyan universities Furthermore Ramiacuterez-
Correa et al (2015) studied gender behavior in relation to the studentsrsquo acceptance of TSL in Chile and
Spain Their findings revealed that there is an insignificant difference between male and female students
in the use of TSL
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 186
The year of study of a student is perceived as the level of education in this paper As per the level of
education Damanpour and Schneider (2006) revealed that education level contributes to the adoption of
innovations Technology-supported learning is perceived as something new hence an innovation
Whereas many studies have been carried out on age and gender few studies seem to focus on the
contribution of level of education to the adoption of technological innovations and less so in developing
economies
It should be noted that the definition of TSL in this paper considers the interaction between
organizational and individual factors This implies that organizational factors impact the individual
factors in relation to the adoption of TSL and vice versa
Interaction between Factors of Adoption of Technology-Supported Learning and Their Impact on Technology Supported Learning
Scholars often wonder whether the individual (student) should adapt to the organization or whether the
organization (eg university) should adapt to the individual (Lippman 2013) Lippman observes that
debatably the preceding statements are incorrect It is better to ask ldquoHow do organizations shape the
individualrdquo In turn ldquoHow does the individual impact organizationsrdquo In his argument the university
can be composed of the students other individuals and the formal physical environment Singh et al
(2005) argue that the structure of organizations has changed They indicate that TSL is part and parcel of
the organization Organizational characteristics can impact on a studentsrsquo ability to adopt TSL
Universities are usually expected to provide policies time for interaction financial support and
commitment to the students in relation to the adoption of TSL (Shah amp Cheng 2019 The amp Usagawa
2018) Students have to be in harmony with the university mission in order for the university to achieve
organizational success University TSL policy gives structure to how students should learn assess and
improve their TSL skills in a university (Makerere University Council personal communication
January nd 2004) Maina and Njuki (2015) argue that organizational TSL policies influence the
adoption of TSL The Makerere University Council (personal communication September nd 2015)
highlights that TSL policies boost pedagogical practices and improve end user skills If students are
familiar with university TSL policies chances are high that their intention innovativeness and
acceptance of TSL will be high
The time students take in interacting with ICT is an important issue in learning environments (Salinas
2004) Drent and Meelissen (2008) argued that time can be assessed according to experimenting
interacting and reflecting with ICT Time has an impact on the adoption of TSL (Shah amp Cheng 2019)
among students Developing economies have been reported to have limited e-resources which reduces
individual ability to experiment with such resources The more students experiment with ICT the more
their intention to use innovativeness and acceptance of TSL
Universities are expected to assist students through financial support to boost their adoption of TSL
(Angolia amp Pagliari 2016) They indicate that TSL comes with new support requirements Additionally
they assert that financial support enhances adoption of TSL among students in higher education
institutions They highlight that in cases where institutions often purchase TSL facilities for the students
the TSL adoption rates tend to be high
University management should be committed to supporting students to boost their adoption of TSL
(Bhardwaj amp Goundar 2018) This can be achieved through training students on how to use TSL
facilities (Kim et al 2019) Students perceive that institutional support is one of the enablers for their
adoption of TSL (Okai-Ugbaje 2020)
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 187
According to Lippman (2013) studentsrsquo age gender and level of education influence their organizations
This can be observed through variations in the use of TSL policies in place time one takes interacting
with ICTs making use of resources and also participating in activities within an organization Literature
indicates that TSL policies are common within learning institutions (Drent amp Meelissen 2008) Students
can get acquainted with these policies take time to practise with ICT use acquired TSL facilities in the
university and avail themselves to receive information from university management about TSL
Whenever a new technology is adopted it finds a society with inequalities in terms of age gender and
level of education Thus understanding the impact of age gender and level of education in the adoption
of TSL in organizations is paramount Maina and Nzuki (2015) indicate that age is an important factor in
understanding adoption of innovations in learning organizations Pereira et al (2018) indicate that
adoption of technological innovations usually takes place at an early age Adewole-Odeshi (2014)
amplifies that older people tend to have low interaction with the learning organizations resulting in low
adoption of technological innovations in such organizations
The relationship between gender and different environments has been testified (Lee amp Pituch 2002
Martin 1991) Lee and Pituch (2002) suggested that gender should not be left out in information
technology (IT ) adoption models An early study by Martin (1991) on gender differences in technology
adoption and telephone use found that womenrsquos use of the telephone for socialization purposes helped
to expand its use in both residential and business areas Odewumi et al (2018) indicate that females are
disadvantaged when it comes to the adoption of information technology
Damanpour and Schneider (2006) reveal that education level is an individual factor They continue to
argue that education is an important aspect of the adoption of innovations Maina and Nzuki (2015)
agree that level of education impacts on the learning organization during the adoption of innovations In
some instances education is viewed as a management strategy that can ease implementation of specific
innovations in particular organizations (Ferreira et al 2015) There seems to be little research on how
the level of education impacts on the learning organization during the adoption of innovations this study
acted as a basis to fill the gap A first-year student may have no knowledge of the TSL policy in a
particular learning institution which may affect their use of TSL facilities
Theoretical Underpinnings of the Study
The interactions between organizational and individual factors have been presented indicating the
complexities involved These interactions were studied with different theoretical underpinnings Factors
can be studied from a theoretical point of view that seeks to predict TSL from both organizational
(macro) and individual (micro) perspectives (Hardaker amp Singh 2011) Sometimes referred to as the
ldquoduality of structurerdquo factors can be drawn from the works of Giddens lsquotheory of structurationrsquo who
argues that macro and micro perspectives are interlinked Giddens theory is mapped to that of (Rogers
2003)rsquos Diffusion of Innovations Theory to ensure that the factors of adoption of TSL are objectively
measured For instance individual (student) was operationalized according to factors of age gender and
level of education The concept of adoption of TSL has been operationalized as intention to use
innovative use and acceptance of TSL Students can perceive that the factors encourage the adoption of
TSL or not The factors that predict successful adoption of TSL have been studied by using the
conceptual framework in Figure 1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 188
Figure 1
The Conceptual Framework of Predictors of Successful Adoption of Technology- Supported
Learning (TSL) in Universities in Uganda
Gestalts Perspective in this Study
To represent the complex interactions we have incorporated Venkatraman (1989)rsquos Gestalts fit which is
an alignment perspective Venkatraman indicates that alignment aims at balancing related organizational
components This is usually done with the aim of achieving organizational success Gestalts fit has been
achieved by configuring factors that are unique tightly integrated and fairly stable We argue that
measuring organizational and individual factors using a linear model is not appropriate Thus alignment
as Gestalts was adopted to identify those configurations of organizational and individual factors that
predict the adoption of TSL in universities
If configurational factors of the framework (ie organizational and individual factors) are well aligned
then there is greater interaction and thus an increase in the adoption of TSL On the other hand if the
elements are misaligned the level of adoption of TSL is low Thus the following hypotheses were tested
by the researchers The greater the alignment between the organizational and individual factors the more
the i) intention to use ii) innovative use and iii) acceptance of TSL in universities will be
Table 1 provides the definitions of these factors In the conceptual framework the third element is an
outcome of the interaction or interplay between the first and second variables
Table 1
Factors Constructs Employed in the Study
Factors Constructs Operationalization References
Organization Goal of TSL policy availability of time
to experiment with ICT availability of
financial support and commitment of
management
Rogers 2003 Shah amp Cheng
(2019)
Individual (student) Student age gender and level of
education
Glazier et al (2019)
Alignment
Between 1 amp 2
Organization (1) Individual
(2)
Adoption of TSL
in universities in
Uganda (3)
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 189
Factors Constructs Operationalization References
Interaction The interaction between the main factors
ie organization and the individual
affect each other
Drazine amp Van de Ven (1985)
Perception This is the studentrsquos perspective that
indicates whether the factors encourage
adoption or not
Gerasimova et al (2018)
Alignment Level of coherence Venkatraman (1989)
Adoption of TSL Intention to use innovative use and
acceptance of TSL
Rogers (2003) Davis (1989)
METHODOLOGICAL FRAMEWORK
To investigate the predictors of the successful adoption of TSL among students the quantitative survey
mixed and cross-sectional research designs were used (Creswell 2014 Greene et al 1989) A recent
study by Shah and Cheng (2019) carried out on studentsrsquo perceptions used a quantitative research
design Thus the same design was adopted for this study In quantitative designs surveys are usually
used The researchers used a survey to collect data from a total of 184 students The survey was
structured into four main parts background information adoption of TSL organizational and individual
factors Bhardwaj and Goundar (2018) in their study on studentsrsquo perceptions on TSL used a mixed
research approach The researchers adopted the said research approach whereby the largely quantitative
and little qualitative techniques were used
Besides lecturers the population of study included students from both Makerere and Gulu universities
Students were chosen because they are the main users of TSL (Bhardwaj amp Goundar 2018) and they are
faced with challenges in using this type of learning (Gerasimova et al 2018) Purposive and simple
random sampling were used for quantitative data The given universities were purposively chosen
because of the level of knowledge and use of TSL Simple random sampling was used at departmental
level to collect quantitative data from students of agricultural sciences because they are among the main
users of TSL facilities at this level Purposive homogeneous sampling was used for qualitative data A
total of six students were interviewed to complement the questionnaire data
The study took place at a particular point in time hence it was cross-sectional in nature Internal and
external validity checks were used (Bhattacherjee 2012) Internal validity was achieved by omitting
extraneous variables so that changes in the response to variables is caused by the hypothesized
explanatory variables External validity was achieved by generalizing from Makerere and Gulu
universities to other universities These two universities were chosen because their lecturers have been
motivated earlier their students would have had more exposure to the technology adoption and with that
experience it would be appropriate to capture their perspectives Validity of the student qualitative
instrument was achieved through use of research experts who were used to validate whether the content
in the instrument could get the data required (Ozkan amp Koseler 2009)
Additionally the developed question concepts were derived from past relevant studies This can be
related to Bhardwaj and Goundar (2019) who captured studentsrsquo perceptions on TSL based on the
modification of concepts from relevant past studies Studies on studentsrsquo perceptions taking a
quantitative approach are usually carried out using reliability tests Kim et al (2019) carried out a
reliability test on a questionnaire that was administered to undergraduate students in a university in
Korea using Cronbachrsquos alpha Similarly the researchers used the same alpha to test questions in the
student self-administered questionnaire The outcome variable of the adoption of TSL was
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 190
operationalized as intention to use innovative use and acceptance of TSL with Cronbach alphas of 064
067 070 respectively The organizational factors had a Cronbach alpha of 073 The researchers
followed ethics guidelines to accomplish the study
RESULTS AND ANALYSIS
Background Information
The majority (821) of the students were aged between 21 and 30 years old This is in line with
Bhardwaj and Goundar (2018) who indicated that the majority of the student respondents were between
21 to 30 years old The majority (641) of the student respondents were male while 359 were female
respondents This is in line with Zuvic-Butorac et al (2011) who found that female students
concentrated on art subjects while their male counterparts were in engineering natural science and ICT
Most (410) of the students were in their second year of study followed by first year students (ie
320) The majority of the students (ie 940) had access to email Few (386) students had laptops
This is because these students may not be in position to afford such devices Most (592) of the
respondents revealed that there are functional TSL laboratories in their universities Most of the students
(571) were affiliated to Gulu University For descriptive analysis of means and standard deviations
for selected research variables see Tables 2 and 3 All the data simulations were based on a Likert scale
of 5 Descriptive analysis of the individual (student) presenting modal age gender and level of education
of the whole population of students (ie N =184) is shown in Table 3
Descriptive Statistics
Table 2
Descriptive Statistics for Selected Research Variables (N =184)
Variable Brief Description of Variables M a Min Max SD
Adoption of TSL
Intention to Use
ITU1 Computers 445 1 5 0979
ITU2 CD-ROMs 283 1 5 1468
ITU3 Web-based learning 384 1 5 1344
ITU4 Video conferencing 359 1 5 1449
ITU5 University TSL environments eg Black-Board 366 1 5 1425
Innovative Use
INU1 I am able to expound on what lecturers have provided to me in class using
the Internet
379 1 5 1334
INU2 I am able to make presentations in text audio and visual 380 1 5 1424
INU3 I am able to communicate with other students through online discussions
emails wikis and WhatsApp
371 1 5 1496
Acceptance
ACC1 Computers 452 1 5 0941
ACC2 CD-ROMs 296 1 5 1536
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 191
Variable Brief Description of Variables M a Min Max SD
ACC3 Web-based learning 375 1 5 1388
ACC4 Video conferencing 359 1 5 1376
ACC5 University TSL environments eg Black-Board 361 1 5 1536
Organizational Factors
GUELP1 Goal of university TSL policy 297 1 5 1408
ATIEXICT1 Availability of time to experiment with ICT 322 1 5 1366
AFS1 Availability of financial support 273 1 5 1544
COMAN1 Commitment of management 304 1 5 1362
a A score of 350 indicates that the person has and there was ldquoeg intention to use TSL encouragement
on use of TSL facilities and ldquohindrance to the progress of TSL ISsrdquo on the five-point Likert scale of
1(Very little or no intention to use TSL encouragement on use of TSL facilities and hindrance to the
progress of TSL ISs ) and 5(Very much intention to use TSL greatest encouragement on use of TSL
facilities and very much hindrance to the progress of TSL ISs)
Students had lsquomuchrsquo intention to use TSL facilities For instance they had lsquomuchrsquo intention to use
computers (ITU1) The students had lsquomuchrsquo innovative use of TSL (for instance they were able to make
presentations in text audio and video INU2) They also indicated very much acceptance of TSL For
instance they had very much acceptance of computers (ACC1)
See Table 3 for most frequent characteristics of each individual in the whole student population (ie N
=184)
Table 3
Individual Factors (N = 184)
Individual Factors Rate of Occurrence Most Frequent
Individual Factors
AGE Most frequent age of students 25 Years
GEN Most frequent gender of students Male
LEDUC Most frequent year of study of students Year 2
Cluster Analyses
The researchers used the k-means clustering algorithm with the help of Statistica Software version 133
to generate six clusters The data were standardized Whereas several simulations were carried out (ie1
2 3 4 5 and 6) only the sixth simulation showed acceptable results All 6 simulations yielded p values
less than 005 (see Table 4) Table 4 indicates the measurement of the organizational factors and
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 192
adoption of TSL in universities in Uganda across the six student clusters Table 5 shows the
measurement of the individual factors across the said clusters
Table 4
Cluster Analysis and Analysis of Variance for Students
Cluster
Variable 1
(n = 37)
2
(n = 38)
3
(n = 19)
4
(n = 42)
5
(n = 24)
6
(n = 24)
ANOVA
F p
Adoption of TSL
Intention to Use TSL
ITU1 011 024 002 032 048 -161 244 00
ITU2 -007 -074 033 069 -014 -005 1109 00
ITU3 -101 037 035 058 039 -072 2502 00
ITU4 -084 031 031 059 031 -079 1893 00
ITU5 -056 022 -006 059 029 -078 1159 00
Innovative Use of TSL
INU1 -025 051 -024 065 -013 -122 2075 00
INU2 014 029 -142 049 052 -092 2671 00
INU3 -051 044 -128 061 049 -045 2449 00
Acceptance of TSL
ACC1 023 023 007 039 034 -179 3439 00
ACC2 -021 -085 050 092 018 -052 2579 00
ACC3 -087 041 007 064 033 -081 2219 00
ACC4 -100 027 029 067 057 -086 3169 00
ACC5 -065 001 -013 064 066 -069 1529 00
Organizational Factors
GUELP1 004 032 -024 078 -099 -075 2078 00
ATIEXICT1 019 -051 -069 089 -009 -040 1636 00
AFS1 012 -051 -044 105 -053 -036 2228 00
COMAN1 001 -017 -057 074 -018 -039 835 00
Note Positive values are indicated in bold while negative ones are not in bold
Table 5
Individual Factors per Cluster
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
AGE Most frequent
age of
students
26
Years
25
Years
25
Years
25
Years
26
Years
24
Years
356 00
GEN Most frequent
gender of
students
Male Equal
number
of male
and
female
Female Male Male Male 426 00
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 193
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
LEDUC Most frequent
year of
study of
students
Year 2 Year 2 Year 1 Year 2 Year 4 Year 1 409 00
Qualitative Analysis
Thematic analysis was used in analyzing qualitative data We used Braun and Clarke (2006)rsquos six
thematic analysis steps of familiarization generating initial codes searching reviewing defining and
naming themes and producing a report Studentsrsquo data comprised student interview data items from
which initial extracts were made Familiarization was carried out by reading and re-reading the said data
items Generating initial codes was achieved through capturing features of interest from the student data
set Searching was achieved through grouping student data relevant to potential themes Defining and
naming was achieved by categorizing the themes Finally a report about the student data was produced
The researchers used the most significant interview data that could support the quantitative results
presented in this paper in the discussion of findings section Thus the discussion of findings is
integrative
DISCUSSION OF FINDINGS
In this section qualitative findings have been integrated with the quantitative ones The letter lsquoSrsquo
denotes student Cluster 1 students were ranked third as far as the adoption of TSL is concerned because
of the quite weak alignment between the configurational factors For instance the students had no
intention to use web-based technology This was confirmed by student S5 who revealed that she did not
understand web-based learning These students could not interact with their colleagues using TSL
facilities Students in this cluster never embraced video conferencing technology because it is limited as
reflected in the main themes by the students S1 S3 and S5 However these students had the intention to
use computer technology This is consistent with student S1 who commented that ldquoI have the intention
to use computers for academic purposesrdquo They also had innovative use of TSL shown through their
ability to incorporate text audio and visual technology Furthermore these students accepted computer
technology This is supported by students S1 S2 and S6 who revealed that they use computers because
of the current education trend which demands them to be computer literate for academic purposes and
they are easy to work with
Further analysis of this cluster indicates that the organizational factors encourage these students to use
TSL facilities (see Table 4) Qualitative results from students S1 S4 and S3 respectively had the
following implications on the organizational factors
bull the goal of the TSL learning policy encourages the use of TSL facilities at a minimal level
bull students practise with ICT and also believe that the university indirectly supports them financially by
providing limited wireless fidelity
bull the university management is supportive by designing sessions on how to use computers
A typical student in this cluster was 26 years old male by gender and in his second year of study (see
Table 5) While these students have similar characteristics with those of Cluster 6 they have tried to
adopt TSL facilities compared Cluster 6 students because of their experience with such facilities
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 194
Cluster 2 students ranked second as far as adoption of TSL is concerned For example students in this
cluster revealed lsquomuchrsquo intention to use TSL For instance student S1 confirmed that ldquoWeb-based
learning offers more informationrdquo Students in this cluster were lsquovery muchrsquo capable of expounding on
what lecturers had provided to them in class using the Internet This was through ldquosurfingrdquo the Internet
using the Google search engine as revealed by student S1 Students in this cluster had lsquomuchrsquo
acceptance of TSL facilities such as web-based facilities This is because web-based learning can be
used for research work and expounding on what is taught in class by lecturers as revealed by student S1
This is confirmed by a recent study by Chopra et al (2019) that indicates that students are satisfied by
web-based technology
In relation to the organizational factors students in Cluster 2 agreed that the goal of university TSL
policy encourages their use of TSL facilities The qualitative results suggest that e-discussions can
compel students to use TSL facilities as revealed by Student S3 On average students in this cluster
were aged 25 years the number of male students was equivalent to that of female ones and they were in
their second year of study (see Table 5) These students could be better adopters than those of Cluster 1
because they seemed to have an equal gender distribution Such distribution may account for an unequal
educational technology use among Cluster 1 and 2 students who enjoyed a similar learning experience
(see Tables 4 and 5) Students of this cluster seemed to be better adopters than those of Clusters 1 3 5
and 6 because of their ability to make use of the TSL policy to their advantage (see Tables 4 and 5)
Cluster 3 students were low adopters of TSL because of low alignment between the configurational
factors thus ranked fifth as far as adoption of TSL is concerned These students lacked innovative use of
TSL facilities implying that these students cannot use such facilities to improve their learning
capabilities The same students however registered lsquovery muchrsquo acceptance of CD-ROMs (see Table 4)
This could be because this medium is a dependable way of accessing content by students (Kisanga amp
Ireson 2015)
Students in Cluster 3 perceived that the organizational factors never contributed to their use of TSL
facilities in any way (see Table 4) For example students had no time to experiment with ICT This
could be because students never practise with ICT due to the fact that the course is ldquohecticrdquo and the IT
laboratories are usually closed over the weekend as revealed by student S1 The average age gender
and level of education of a student in this cluster is 25 years female and first-year respectively (see
Table 5) These could be lower adopters of TSL than members of Clusters 2 and 5 because of their
gender Female respondents are disadvantaged when it comes to the use of information technology
(Odewumi 2018) Another plausible reason for the low adoption levels in Cluster 3 compared to those
in Clusters 2 and 1 could be the lack of innovative use of TSL (see Table 4)
Cluster 4 students were the greatest adopters of TSL among the six clusters This is because they had the
lsquogreatestrsquo alignment between the configurational factors These students are eager to use ICT innovative
and embraced TSL They are eager to use CD-ROM technology because such technology is cheap and
stores information as confirmed by students S1 and S6 They can innovatively expound on what
lectures have provided to them in class using the Internet with the help of search engines (such as
Google) as indicated by student S1 They have embraced video conference technology Students S1 S3
and S5 confirmed that they were able to imitate the limited video conferencing learning using the
WhatsApp facility
Students in Cluster 4 perceived that the organizational factors encouraged their use of TSL facilities
High scores were registered on the goal of the university TSL policy time to experiment with ICT
financial support and commitment of university management For instance during the interview process
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 195
student S3 revealed that ldquoa discussion policy for example may improve adoption of [TSL] because
once e-discussions are made they can compel one to use the [TSL] facilitiesrdquo The result from the
interview process on time to experiment with TSL conflicts with the cluster one whereby the majority
of the students never found time to practise with TSL facilities Shah and Cheng (2019) however
indicate that time influences the adoption of TSL facilities Quantitative findings in this cluster on
financial support could be related to those of student S3 who indicated that there was indirect financial
support by their university through the provision of wireless technology On the issue of management
commitment findings are in line with those of student S4 who felt that university management was
committed because they designed computer literacy sessions for them A typical student in this cluster
was 25 years old male by gender and in year 2 of study (see Table 5) This cluster (n = 42) had the
majority of the student respondents among the six clusters
The alignment of the configurational factors in Cluster 5 seemed to be lsquoweakerrsquo than that of Cluster 1
thus this cluster was ranked fourth Whereas the students in this cluster indicated lsquovery muchrsquo adoption
of TSL in some instances the configurational variables registered low scores For instance they had
very much acceptance of TSL environments yet they seemed not to be familiar with the TSL policy
The result on acceptance of TSL environments is parallel to that of Bond et al (2018) who indicated that
such environments are commonly used by students in higher education institutions in Germany The
result on the TSL policy was confirmed by student S4 who revealed that the TSL policy is not
effectively implemented in the university A normal student in this cluster was 26 years old male by
gender and in year 4 of the study (see Table 5) These students could be better adopters of TSL than
those of Clusters 3 and 6 because of their long-time experience with TSL as reflected in their year of
study compared to the said clusters (see Tables 4 and 5) It is not surprising this cluster had the best
distributions of ICTs among students
Similar to Cluster 5 Cluster 6 had 24 respondents (see Table 4) However students in this cluster are
coincidentally ranked as non-adopters of TSL among the six clusters (see Tables 4 and 5) This is
because there is no alignment between the configurational factors resulting in no adoption of TSL
These students were not willing to use IT could not modify their learning capabilities using IT and had
not realised the value of IT tools All 24 respondents in this cluster lsquoconcurredrsquo that the organization
never encouraged their use of TSL facilities This could imply that students were not involved at all
during the adoption of TSL Shah and Cheng (2019) reveal that students perceive that juggling work and
study caring for children financial difficulty and academic writing among other factors affect their
ability to adopt TSL On average students in this cluster were 26 years old male by gender and in year
1 of their study Being in their first year of study could imply that they had little experience with TSL
CONCLUSION
Identification of predictors of successful adoption of TSL among students was achieved using the
Gestalts approach Students perceived that organizational and individual factors predict successful
adoption of TSL Cluster 4 is the most coherent and as such adopted TSL most This is because the
organizational and individual factors were most aligned For example when students in this cluster are
financially supported and are in their second year of study they are eager to use to be innovative with
and embrace TSL And because of their eagerness innovativeness and ability to embrace TSL they have
accumulated more experience than others Cluster 6 students are non-adopters because they are more
inexperienced with TSL than the rest of the students
There seems to be a gap in the use of the non-linear techniques (eg clustering technique) in studies on
studentsrsquo perceptions Most studies for instance Chopra et al (2019) Gerasimova et al (2018) and Shah
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 196
and Cheng (2019) who have measured student perceptions have used linear techniques Thus this study
has closed this gap This study is a benchmark for universities in developing economies to integrate TSL
at university level For instance it should be noted that in order to achieve successful adoption of TSL
among students in universities management must be involved Nabushawo et al (2018) suggest that the
commitment of management can be achieved by collaborating with and training the users of TSL ISs
Since the world is challenged by Corona Virus Disease (COVID) this study can be used as model to
avail learning materials to students without spreading this disease
It should be noted that the rate of adoption of TSL among students is still low yet they have advanced in
age This contradicts Pereira et al (2018) who indicated that adoption of TSL usually takes place at an
early age It is therefore recommended that students should be supported to adopt TSL during their
earlier career years so that universities in Uganda can benefit from this innovation This can be done by
introducing TSL at primary level Universities need to strengthen their management capabilities such as
increasing the time studentsrsquo have to experiment with ICTs Further research is required to develop
strategies that can be adopted to enhance adoption of TSL among students at earlier ages Although this
study was carried out at a particular point in time it can also be carried out longitudinally There are
many indicators of the organization individual (student) and adoption of TSL besides those presented in
the conceptual framework Further research can be carried out on those Besides organization and
individual factors there is need to know the role of other factors in the adoption of TSL among students
While students from only two public universities were considered for this study students from other
universities can be considered as well
ACKNOWLEDGMENTS
The researchers want to thank the Almighty God for the gift of knowledge wisdom and understanding
in the writing of this paper The researchers also thank the Organization for Women in Science for the
Developing World (OWSD) and the Swedish International Development Agency (SIDA) for their
financial support in carrying out the study
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Acosta M L Sisley A Ross J Brailsford I Bhargava A Jacobs R amp Anstice N (2018) Student acceptance of e-
learning methods in the laboratory class in optometry PLOS ONE 13(12) 1-15
httpsdoiorg101371journalpone0209004
Adewole-Odeshi E (2014) Attitude of students towards e-learning in South-West Nigerian universities An application of
technology acceptance model Library Philosophy and Practice Article 1035
Angolia M G amp Pagliari L R (2016) Factors for successful evolution and sustainability of quality distance education
Online Journal of Distance Learning Administration 19(3)
Ayele B A amp Birhanie W K (2018) Acceptance and use of e-learning systems The case of teachers in technology
institutes of Ethiopian universities Applied Informatics 5(1) 1-11 httpsdoiorg101186s40535-018-0048-7
Back D A von Malotky J Sostmann K Peters H Hube R amp Hoff E (2019) Experiences with using e-learning tools
in orthopedics in an uncontrolled field study application Orthopaedics amp Traumatology Surgery amp Research
105(2) 389-393 httpsdoiorg101016jotsr201901002
Bhardwaj A amp Goundar S (2018) Students perspective of elearning and the future of education with MOOCs
International Journal of Computer Engineering 7(5) 248-260
Bhattacherjee A (2012) Social science research Principles methods and practices Textbooks Collection
httpscholarcommonsusfeduoa_textbooks3
Bond M Mariacuten V I Dolch C Bedenlier S amp Zawacki-Ritcher O (2018) Digital transformation in German higher
education Student and teacher perceptions and usage of digital media International Journal of Educational
Technology in Higher Education 15(48) httpsdoiorg101186s41239-018-0130-1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 197
Braun V amp Clarke V (2006) Using thematic analysis in psychology Qualitative Research in Psychology 33 77-101
Chopra G Madan P Jaisingh P amp Bhaskar P (2019) Effectiveness of e-learning portal from studentsrsquo perspective A
structural equation model (SEM) approach Interactive Technology and Smart Education 16(2) 94-116
httpsdoiorg101108ITSE-05-2018-0027
Creswell J W (2014) Research Design Qualitative quantitative and mixed methods approaches (4th ed) Sage
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Damanpour F amp Schneider M (2006) Phases of the adoption of innovation in organisations Effects of environment
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Davis F D (1989) Perceived usefulness perceived ease of use and user acceptance of information technology MIS
Quarterly 13(3) 319ndash340 httpsdoiorg102307249008
Drazin R amp Van de Ven A H (1985) Alternative forms of fit in contingency theory Administrative Science Quarterly
30(4) 514-539 httpsdoiorg1023072392695
Drent M amp Meelissen M (2008) Which factors obstruct or stimulate teacher educators to use ICT innovatively
Computers amp Education 51 187ndash199 httpsdoiorg101016jcompedu200705001
Eze S C Chinedu-Eze V C amp Bello A O (2018) The utilisation of e-learning facilities in the educational delivery
system of Nigeria A study of M-University International Journal of Educational Technology in Higher Education
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Ferreira A Teixeira A L amp Dantas A R (2015) Non-technological innovation activities mediate the impacts of the
intra- and extra-organisational contexts on technological innovation outputs Enterprise and Work Innovation
Studies 11 9-43
Gerasimova V G Melamud M R Tutaeva D R Romanova Y D amp Zhenova N A (2018) The adoption of e-learning
technology at the Faculty of Distance Learning of Plekhanov Russian University of Economics Journal of Social
Studies Education Research 9(2) 172-188
Glazier R A Hamann K Pollock P H amp B Wilson B M (2019) Age gender and student success Mixing face-to-face
and online courses in political science Journal of Political Science Education 16(2) 142-157 httpsdoiorg1010801551216920181515636
Greene J C Caracelli V J amp Graham W F (1989) Toward a conceptual framework for mixed method evaluation
designs Educational Evaluation and Policy Analysis 11(3) 255-274 httpsdoiorg1023071163620
Gwamba G Renken J Nampijja J Mayende G amp Muyinda P B (2018) Contextualisation of e-learning systems in
higher education institutions In M Auer amp T Tsiatsos (Eds) Interactive mobile communication technologies and
learning Proceedings of the 11th IMCL conference (pp 44-55) Springer
Hardaker G amp Singh G (2011) The adoption and diffusion of eLearning in UK universities A comparative case study
using Giddenss theory of structuration Campus-Wide Information Systems 28(4) 221ndash233
httpsdoiorg10110810650741111162707
Kim H J Hong A J amp Song H (2019) The roles of academic engagement and digital readiness in studentsrsquo
achievements in university e-learning environments International Journal of Educational Technology in Higher
Education 16(21) 1-18 httpsdoiorg101186s41239-019-0152-3
Kimiloglu H Ozturan M amp Kutlu B (2017) Perceptions about and attitude toward the usage of e-learning in corporate
training Computers in Human Behavior 72 339-349 httpsdoiorg101016jchb201702062
Kisanga D amp Ireson G (2015) Barriers and strategies on adoption of e-learning in Tanzanian higher learning institutions
Lessons for adopters International Journal of Education and Development using Information and Communication
Technology (IJEDICT) 11(2) 126-137
Lee Y-K amp Pituch K (2002 December 10ndash13) Moderators in the adoption of e-learning An investigation of the role of
gender [Article] The Second International Conference on Electronic Business Taipei Taiwan
Lippman P C (2010) Can the physical environment have an impact on the learning environment CELE Exchange
httpsdoiorg1017875km4g21wpwr1-en
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The African Journal of Information Systems Volume 13 Issue 2 Article 3 198
Maina M K amp Nzuki D M (2015) Adoption determinants of e-learning management system in institutions of higher
learning in Kenya A case of selected universities in Nairobi metropolitan International Journal of Business and
Social Science 6(2) 233ndash248
Martin M (1991) The culture of the telephone In PD Hopkins (Ed) Sexmachine Readings in culture gender and
technology (pp 50-74) Indiana University Press
Moakofhi M Leteane O Phiri T Pholele T amp Sebalatlheng P (2017) Challenges of introducing e-learning at
Botswana University of Agriculture and Natural Resources Lecturersrsquo perspective International Journal of
Education and Development using ICT 13( 2) 4-20
Nabushawo H M Muyinda P B Isabwe G M N Prinz A amp Mayende G (2018) Improving online interaction among
blended distance learners at Makerere University In M E Auer D Guralnick amp I Simonics (Eds) Advances in
Intelligent Systems and Computing (pp 63-69) Springer httpsdoiorg101007978-3-319-73210-7_8
Odewumi M O Yusuf M O amp Oputa G O (2018) UTAUT model Intention to use social media for learning interactive
effect of postgraduate gender in South-West Nigeria International Journal of Education and Development using
Information and Communication Technology (IJEDICT) 14(3) 239-251
Okai-Ugbaje S Ardzejewska K amp Imran A (2020) Readiness roles and responsibilities of stakeholders for sustainable
mobile learning adoption in higher education Education Sciences 10(3) 49-69
httpsdoiorg103390educsci10030049
Ozkan S amp Koseler R (2009) Multi-dimensional studentsrsquo evaluation of e-learning systems in the higher education
context An empirical investigation Computers amp Education 53(4) 1285ndash1296
httpsdoiorg101016jcompedu200906011
Parlakkılıccedil A (2014) Change management in transition to e-learning system Qualitative and Quantitative Methods in
Libraries 3(3) 637ndash651
Pereira A Martins P Morgado L amp Fonseca B (2018) Technological proposal using virtual worlds to support
entrepreneurship education for primary school children In M E Auer D Guralnick amp I Simonics (Eds)
Advances in Intelligent Systems and Computing (pp 124-132) Springer
Ramiacuterez-Correa P E Arenas-Gaitaacuten J amp Rondaacuten-Cataluntildea F J (2015) Gender and acceptance of e-learning A multi-
group analysis based on a structural equation model among college students in Chile and Spain PLOS ONE
10(10) 1-17 httpsdoiorg101371journalpone0140460
Rhema A amp Miliszewska I (2014) Analysis of student attitudes towards e-learning The case of engineering students in
Libya Issues in Informing Science and Information Technology 11 169-190 httpsdoiorg10289451987
Rogers E M (2003) Diffusion of innovations (5th ed) Free Press
Salinas J (2004) Cambios metodoloacutegicos con las TIC Estrategias didaacutecticas y entornos virtuales de ensentildeanza-aprendizaje
Bordoacuten 56(3-4) 469-481
Selim H M (2007) Critical success factors for e-learning acceptance Confirmatory factor models Computers amp
Education 49(2) 396ndash413 httpsdoi101016jcompedu200509004
Shah M amp Cheng M (2019) Exploring factors impacting student engagement in open access courses Open learning The
Journal of Open Distance and E-Learning 34(2) 187-202 httpsdoiorg1010800268051320181508337
Singh G ODonoghue J amp Worton H (2005) A study into the effects of elearning on higher education Journal of
University Teaching and Learning Practice 2(1) 13-24
Tchamyou V S (2017) The role of knowledge economy in African business Journal of the Knowledge Economy 8(4)
1189ndash1228 httpsdoiorg101007s13132-016-0417-1
The M M amp Usagawa T (2018) A comparative study of studentsrsquo readiness on e-learning education between Indonesia
and Myanmar American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS) 40(1)
113-124
Venkatraman N (1989) The concept of fit in strategy research Toward verbal and statistical correspondence Academy of
Management Review 9(3) 513-525 httpsdoiorg102307258177
Zuvic-Butorac M Nebic Z amp Nemcanin D (2011) Establishing an institutional framework for an e-learning
implementation Experiences from the University of Rijeka Croatia Journal of Information Technology Education
Innovations in Practice 10 43-56 httpsdoiorg10289451364
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Recommended Citation
-
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Cover Page Footnote
-
- tmp1624440487pdfGS9c9
-
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 184
Universities in developing economies in particular have adopted technology-supported learning
information systems (TSL ISs) to boost the knowledge society (Tchamyou 2017) Since students are the
key users of TSL (Bhardwaj amp Goundar 2018) in universities understanding their perspective in the
adoption of TSL would be paramount to educational re-engineering In addition students face
challenges during their encounter with TSL (Gerasimova et al 2018) They indicate that such
challenges or factors include lack of self-discipline and motivation financial implications and lack of
face to face interaction with a tutor Given the fact that these factors in adoption of TSL have a great
impact on students it is worth investigating such factors to augment their (studentsrsquo) learning in
universities
Other writers have reported disparities in who uses technology and at what age they are exposed to it In
order to understand the predictors of adoption and effective use of technology in education the
perspective of students regarding the adoption of technology and their views about what the institutions
should provide to make this adoption possible is critical However not many studies have looked at this
problem from the perspective of students who happen to use the TSL (Acosta et al 2018) In the present
study the researchers investigate the predictors of successful adoption of TSL as perceived by students
The Gestalts approach was adopted given the fact that the predictors are complex and interactional
making it difficult to measure their influence Gestalts is defined as configuration of institutional
components that has achieved a satisfactory high level of coherence (Venkatraman 1989) Gestalts
scholars argue that success is only achieved when the components achieve a satisfactorily high level of
coherence
The present study focuses on two categories of predictors organizational and individual factors The
next section reviews these predictors and how they interact to influence the adoption of TSL A
conceptual framework based on the Gestalts approach is developed and tested with a sample of students
from two institutions of learning in Uganda An elaboration about the approach used in this paper is in
the methodological framework Following this is the results and analysis and then discussion of
findings This paper ends with a conclusion
LITERATURE REVIEW
Definition of Technology-Supported Learning
The change from the traditional curriculum to the digital curriculum has revolutionalized higher
education Technology-supported learning has been defined and measured from different perspectives
by researchers Technology-supported learning has been defined by Hardaker and Singh (2011) ldquoas an
innovation situated in the interplay between structure and individual and how this leads to adoption and
diffusionrdquo (p222) Eze et al (2018) have defined TSL as technology-mediated learning that uses
hardware and software systems to enhance the teaching and learning processes Ayele amp Birhanie
(2018) indicate that TSL is a modern way of delivering learning resources to students in higher learning
institutions In this paper we choose to define TSL as e-learning resulting from the interaction between
the organizational and individual factors Gerasimova et al (2018) elaborates that TSL saves studentsrsquo
time and also reduces travel time associated with the traditional face to face approach TSL may
encompass compact disc read-only-memory (CD-ROMs) digital texts podcasts learning management
systems (LMSs) video-technology and websites among others
While CD-ROMs are no longer used widely today Kisanga and Ireson (2015) indicated at that time that
they were a very reliable way of accessing content by students Digital texts and podcasts have been
presented as vital tools for student knowledge delivery in the medical field (Back et al 2019) Learning
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 185
management systems also play a vital role in the delivery of academic resources to students in
universities (Gwamba et al 2018) Bond et al (2018) indicate that LMSs are commonly used among
students in higher education institutions in Germany Nevertheless a recent study by Kim et al (2019)
indicated that students had no experience with LMSs and video technology Chopra et al (2019)
indicate that students are satisfied with web-based learning
Organizational Factors and Technology-Supported Learning
Organizational factors such as management support user training and financial incentives increase the
adoption of TSL ISs in organizations (Ayele amp Birhanie 2018) Shah and Cheng (2019) argue that
development of TSL policies is an opportunity of revolutionizing universities while engaging students
Back et al (2019) suggest that students should practice with ICTs A study by The and Usagawa (2018)
revealed that if a person practices with ICTs they gain confidence in using such tools Shah and Cheng
(2019) similarly indicate that distance learners are faced with many challenges which may force them to
drop out of universities The students cited juggling work and study caring for children financial
difficulty and academic writing among others as challenges to TSL
Another area of concern raised by Shah and Cheng (2019) was the time spent by a student studying off-
campus Such time involves experimenting with ICTs Furthermore they argue that indicators such as
online learning resources relevant course materials and building student confidence are key to positive
learning Students perceive that commitment of university management in uploading the online
resources subscribing to relevant courses and ensuring that the lecturers build confidence in them
contributes to the adoption of TSL
Students perceived that organizational support plays a vital role in their adoption of TSL (Selim 2007)
A study by Bhardwaj and Goundar (2018) reveals that students perceive that university management
does not support their use of TSL We choose to look at the goal of the TSL policy time to experiment
with ICT financial support and commitment of university management as organizational factors that
can influence studentsrsquo adoption of TSL Additionally Moakofhi et al (2017) argue that studying
organizational factors is essential in understanding technological adoption
Individual Factors and Technology-Supported Learning
Individual factors can be termed as personal factors depending on the author The individual in question
is a student Kimiloglu et al (2017) specify that individual factors can explain the adoption of TSL ISs
Parlakkılıccedil (2014) indicated that age influences the use of information technologies In addition Pereira
et al (2018) uphold that people tend to adopt TSL at an early age Gerasimova et al (2018) specified
that the average age of students who adopted TSL at the Russian University of Economics was 23 years
They revealed that the majority of these students appreciated TSL Another study by Bhardwaj and
Goundar (2018) about studentsrsquo perceptions of TSL shows that the majority of the students engaged in
the study were aged between 21 to 30 years of age
With reference to gender female students showed a preference for humanities and social sciences while
their male counterparts preferred engineering natural science and ICT (Zuvic-Butorac et al 2011)
Nevertheless Kim et al (2019) report that female students are more experienced with TSL than males
Additionally Rhema and Miliszewska (2014) revealed that there is no difference between female and
male students when it comes to the acceptance of TSL in Libyan universities Furthermore Ramiacuterez-
Correa et al (2015) studied gender behavior in relation to the studentsrsquo acceptance of TSL in Chile and
Spain Their findings revealed that there is an insignificant difference between male and female students
in the use of TSL
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 186
The year of study of a student is perceived as the level of education in this paper As per the level of
education Damanpour and Schneider (2006) revealed that education level contributes to the adoption of
innovations Technology-supported learning is perceived as something new hence an innovation
Whereas many studies have been carried out on age and gender few studies seem to focus on the
contribution of level of education to the adoption of technological innovations and less so in developing
economies
It should be noted that the definition of TSL in this paper considers the interaction between
organizational and individual factors This implies that organizational factors impact the individual
factors in relation to the adoption of TSL and vice versa
Interaction between Factors of Adoption of Technology-Supported Learning and Their Impact on Technology Supported Learning
Scholars often wonder whether the individual (student) should adapt to the organization or whether the
organization (eg university) should adapt to the individual (Lippman 2013) Lippman observes that
debatably the preceding statements are incorrect It is better to ask ldquoHow do organizations shape the
individualrdquo In turn ldquoHow does the individual impact organizationsrdquo In his argument the university
can be composed of the students other individuals and the formal physical environment Singh et al
(2005) argue that the structure of organizations has changed They indicate that TSL is part and parcel of
the organization Organizational characteristics can impact on a studentsrsquo ability to adopt TSL
Universities are usually expected to provide policies time for interaction financial support and
commitment to the students in relation to the adoption of TSL (Shah amp Cheng 2019 The amp Usagawa
2018) Students have to be in harmony with the university mission in order for the university to achieve
organizational success University TSL policy gives structure to how students should learn assess and
improve their TSL skills in a university (Makerere University Council personal communication
January nd 2004) Maina and Njuki (2015) argue that organizational TSL policies influence the
adoption of TSL The Makerere University Council (personal communication September nd 2015)
highlights that TSL policies boost pedagogical practices and improve end user skills If students are
familiar with university TSL policies chances are high that their intention innovativeness and
acceptance of TSL will be high
The time students take in interacting with ICT is an important issue in learning environments (Salinas
2004) Drent and Meelissen (2008) argued that time can be assessed according to experimenting
interacting and reflecting with ICT Time has an impact on the adoption of TSL (Shah amp Cheng 2019)
among students Developing economies have been reported to have limited e-resources which reduces
individual ability to experiment with such resources The more students experiment with ICT the more
their intention to use innovativeness and acceptance of TSL
Universities are expected to assist students through financial support to boost their adoption of TSL
(Angolia amp Pagliari 2016) They indicate that TSL comes with new support requirements Additionally
they assert that financial support enhances adoption of TSL among students in higher education
institutions They highlight that in cases where institutions often purchase TSL facilities for the students
the TSL adoption rates tend to be high
University management should be committed to supporting students to boost their adoption of TSL
(Bhardwaj amp Goundar 2018) This can be achieved through training students on how to use TSL
facilities (Kim et al 2019) Students perceive that institutional support is one of the enablers for their
adoption of TSL (Okai-Ugbaje 2020)
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 187
According to Lippman (2013) studentsrsquo age gender and level of education influence their organizations
This can be observed through variations in the use of TSL policies in place time one takes interacting
with ICTs making use of resources and also participating in activities within an organization Literature
indicates that TSL policies are common within learning institutions (Drent amp Meelissen 2008) Students
can get acquainted with these policies take time to practise with ICT use acquired TSL facilities in the
university and avail themselves to receive information from university management about TSL
Whenever a new technology is adopted it finds a society with inequalities in terms of age gender and
level of education Thus understanding the impact of age gender and level of education in the adoption
of TSL in organizations is paramount Maina and Nzuki (2015) indicate that age is an important factor in
understanding adoption of innovations in learning organizations Pereira et al (2018) indicate that
adoption of technological innovations usually takes place at an early age Adewole-Odeshi (2014)
amplifies that older people tend to have low interaction with the learning organizations resulting in low
adoption of technological innovations in such organizations
The relationship between gender and different environments has been testified (Lee amp Pituch 2002
Martin 1991) Lee and Pituch (2002) suggested that gender should not be left out in information
technology (IT ) adoption models An early study by Martin (1991) on gender differences in technology
adoption and telephone use found that womenrsquos use of the telephone for socialization purposes helped
to expand its use in both residential and business areas Odewumi et al (2018) indicate that females are
disadvantaged when it comes to the adoption of information technology
Damanpour and Schneider (2006) reveal that education level is an individual factor They continue to
argue that education is an important aspect of the adoption of innovations Maina and Nzuki (2015)
agree that level of education impacts on the learning organization during the adoption of innovations In
some instances education is viewed as a management strategy that can ease implementation of specific
innovations in particular organizations (Ferreira et al 2015) There seems to be little research on how
the level of education impacts on the learning organization during the adoption of innovations this study
acted as a basis to fill the gap A first-year student may have no knowledge of the TSL policy in a
particular learning institution which may affect their use of TSL facilities
Theoretical Underpinnings of the Study
The interactions between organizational and individual factors have been presented indicating the
complexities involved These interactions were studied with different theoretical underpinnings Factors
can be studied from a theoretical point of view that seeks to predict TSL from both organizational
(macro) and individual (micro) perspectives (Hardaker amp Singh 2011) Sometimes referred to as the
ldquoduality of structurerdquo factors can be drawn from the works of Giddens lsquotheory of structurationrsquo who
argues that macro and micro perspectives are interlinked Giddens theory is mapped to that of (Rogers
2003)rsquos Diffusion of Innovations Theory to ensure that the factors of adoption of TSL are objectively
measured For instance individual (student) was operationalized according to factors of age gender and
level of education The concept of adoption of TSL has been operationalized as intention to use
innovative use and acceptance of TSL Students can perceive that the factors encourage the adoption of
TSL or not The factors that predict successful adoption of TSL have been studied by using the
conceptual framework in Figure 1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 188
Figure 1
The Conceptual Framework of Predictors of Successful Adoption of Technology- Supported
Learning (TSL) in Universities in Uganda
Gestalts Perspective in this Study
To represent the complex interactions we have incorporated Venkatraman (1989)rsquos Gestalts fit which is
an alignment perspective Venkatraman indicates that alignment aims at balancing related organizational
components This is usually done with the aim of achieving organizational success Gestalts fit has been
achieved by configuring factors that are unique tightly integrated and fairly stable We argue that
measuring organizational and individual factors using a linear model is not appropriate Thus alignment
as Gestalts was adopted to identify those configurations of organizational and individual factors that
predict the adoption of TSL in universities
If configurational factors of the framework (ie organizational and individual factors) are well aligned
then there is greater interaction and thus an increase in the adoption of TSL On the other hand if the
elements are misaligned the level of adoption of TSL is low Thus the following hypotheses were tested
by the researchers The greater the alignment between the organizational and individual factors the more
the i) intention to use ii) innovative use and iii) acceptance of TSL in universities will be
Table 1 provides the definitions of these factors In the conceptual framework the third element is an
outcome of the interaction or interplay between the first and second variables
Table 1
Factors Constructs Employed in the Study
Factors Constructs Operationalization References
Organization Goal of TSL policy availability of time
to experiment with ICT availability of
financial support and commitment of
management
Rogers 2003 Shah amp Cheng
(2019)
Individual (student) Student age gender and level of
education
Glazier et al (2019)
Alignment
Between 1 amp 2
Organization (1) Individual
(2)
Adoption of TSL
in universities in
Uganda (3)
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 189
Factors Constructs Operationalization References
Interaction The interaction between the main factors
ie organization and the individual
affect each other
Drazine amp Van de Ven (1985)
Perception This is the studentrsquos perspective that
indicates whether the factors encourage
adoption or not
Gerasimova et al (2018)
Alignment Level of coherence Venkatraman (1989)
Adoption of TSL Intention to use innovative use and
acceptance of TSL
Rogers (2003) Davis (1989)
METHODOLOGICAL FRAMEWORK
To investigate the predictors of the successful adoption of TSL among students the quantitative survey
mixed and cross-sectional research designs were used (Creswell 2014 Greene et al 1989) A recent
study by Shah and Cheng (2019) carried out on studentsrsquo perceptions used a quantitative research
design Thus the same design was adopted for this study In quantitative designs surveys are usually
used The researchers used a survey to collect data from a total of 184 students The survey was
structured into four main parts background information adoption of TSL organizational and individual
factors Bhardwaj and Goundar (2018) in their study on studentsrsquo perceptions on TSL used a mixed
research approach The researchers adopted the said research approach whereby the largely quantitative
and little qualitative techniques were used
Besides lecturers the population of study included students from both Makerere and Gulu universities
Students were chosen because they are the main users of TSL (Bhardwaj amp Goundar 2018) and they are
faced with challenges in using this type of learning (Gerasimova et al 2018) Purposive and simple
random sampling were used for quantitative data The given universities were purposively chosen
because of the level of knowledge and use of TSL Simple random sampling was used at departmental
level to collect quantitative data from students of agricultural sciences because they are among the main
users of TSL facilities at this level Purposive homogeneous sampling was used for qualitative data A
total of six students were interviewed to complement the questionnaire data
The study took place at a particular point in time hence it was cross-sectional in nature Internal and
external validity checks were used (Bhattacherjee 2012) Internal validity was achieved by omitting
extraneous variables so that changes in the response to variables is caused by the hypothesized
explanatory variables External validity was achieved by generalizing from Makerere and Gulu
universities to other universities These two universities were chosen because their lecturers have been
motivated earlier their students would have had more exposure to the technology adoption and with that
experience it would be appropriate to capture their perspectives Validity of the student qualitative
instrument was achieved through use of research experts who were used to validate whether the content
in the instrument could get the data required (Ozkan amp Koseler 2009)
Additionally the developed question concepts were derived from past relevant studies This can be
related to Bhardwaj and Goundar (2019) who captured studentsrsquo perceptions on TSL based on the
modification of concepts from relevant past studies Studies on studentsrsquo perceptions taking a
quantitative approach are usually carried out using reliability tests Kim et al (2019) carried out a
reliability test on a questionnaire that was administered to undergraduate students in a university in
Korea using Cronbachrsquos alpha Similarly the researchers used the same alpha to test questions in the
student self-administered questionnaire The outcome variable of the adoption of TSL was
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 190
operationalized as intention to use innovative use and acceptance of TSL with Cronbach alphas of 064
067 070 respectively The organizational factors had a Cronbach alpha of 073 The researchers
followed ethics guidelines to accomplish the study
RESULTS AND ANALYSIS
Background Information
The majority (821) of the students were aged between 21 and 30 years old This is in line with
Bhardwaj and Goundar (2018) who indicated that the majority of the student respondents were between
21 to 30 years old The majority (641) of the student respondents were male while 359 were female
respondents This is in line with Zuvic-Butorac et al (2011) who found that female students
concentrated on art subjects while their male counterparts were in engineering natural science and ICT
Most (410) of the students were in their second year of study followed by first year students (ie
320) The majority of the students (ie 940) had access to email Few (386) students had laptops
This is because these students may not be in position to afford such devices Most (592) of the
respondents revealed that there are functional TSL laboratories in their universities Most of the students
(571) were affiliated to Gulu University For descriptive analysis of means and standard deviations
for selected research variables see Tables 2 and 3 All the data simulations were based on a Likert scale
of 5 Descriptive analysis of the individual (student) presenting modal age gender and level of education
of the whole population of students (ie N =184) is shown in Table 3
Descriptive Statistics
Table 2
Descriptive Statistics for Selected Research Variables (N =184)
Variable Brief Description of Variables M a Min Max SD
Adoption of TSL
Intention to Use
ITU1 Computers 445 1 5 0979
ITU2 CD-ROMs 283 1 5 1468
ITU3 Web-based learning 384 1 5 1344
ITU4 Video conferencing 359 1 5 1449
ITU5 University TSL environments eg Black-Board 366 1 5 1425
Innovative Use
INU1 I am able to expound on what lecturers have provided to me in class using
the Internet
379 1 5 1334
INU2 I am able to make presentations in text audio and visual 380 1 5 1424
INU3 I am able to communicate with other students through online discussions
emails wikis and WhatsApp
371 1 5 1496
Acceptance
ACC1 Computers 452 1 5 0941
ACC2 CD-ROMs 296 1 5 1536
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 191
Variable Brief Description of Variables M a Min Max SD
ACC3 Web-based learning 375 1 5 1388
ACC4 Video conferencing 359 1 5 1376
ACC5 University TSL environments eg Black-Board 361 1 5 1536
Organizational Factors
GUELP1 Goal of university TSL policy 297 1 5 1408
ATIEXICT1 Availability of time to experiment with ICT 322 1 5 1366
AFS1 Availability of financial support 273 1 5 1544
COMAN1 Commitment of management 304 1 5 1362
a A score of 350 indicates that the person has and there was ldquoeg intention to use TSL encouragement
on use of TSL facilities and ldquohindrance to the progress of TSL ISsrdquo on the five-point Likert scale of
1(Very little or no intention to use TSL encouragement on use of TSL facilities and hindrance to the
progress of TSL ISs ) and 5(Very much intention to use TSL greatest encouragement on use of TSL
facilities and very much hindrance to the progress of TSL ISs)
Students had lsquomuchrsquo intention to use TSL facilities For instance they had lsquomuchrsquo intention to use
computers (ITU1) The students had lsquomuchrsquo innovative use of TSL (for instance they were able to make
presentations in text audio and video INU2) They also indicated very much acceptance of TSL For
instance they had very much acceptance of computers (ACC1)
See Table 3 for most frequent characteristics of each individual in the whole student population (ie N
=184)
Table 3
Individual Factors (N = 184)
Individual Factors Rate of Occurrence Most Frequent
Individual Factors
AGE Most frequent age of students 25 Years
GEN Most frequent gender of students Male
LEDUC Most frequent year of study of students Year 2
Cluster Analyses
The researchers used the k-means clustering algorithm with the help of Statistica Software version 133
to generate six clusters The data were standardized Whereas several simulations were carried out (ie1
2 3 4 5 and 6) only the sixth simulation showed acceptable results All 6 simulations yielded p values
less than 005 (see Table 4) Table 4 indicates the measurement of the organizational factors and
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 192
adoption of TSL in universities in Uganda across the six student clusters Table 5 shows the
measurement of the individual factors across the said clusters
Table 4
Cluster Analysis and Analysis of Variance for Students
Cluster
Variable 1
(n = 37)
2
(n = 38)
3
(n = 19)
4
(n = 42)
5
(n = 24)
6
(n = 24)
ANOVA
F p
Adoption of TSL
Intention to Use TSL
ITU1 011 024 002 032 048 -161 244 00
ITU2 -007 -074 033 069 -014 -005 1109 00
ITU3 -101 037 035 058 039 -072 2502 00
ITU4 -084 031 031 059 031 -079 1893 00
ITU5 -056 022 -006 059 029 -078 1159 00
Innovative Use of TSL
INU1 -025 051 -024 065 -013 -122 2075 00
INU2 014 029 -142 049 052 -092 2671 00
INU3 -051 044 -128 061 049 -045 2449 00
Acceptance of TSL
ACC1 023 023 007 039 034 -179 3439 00
ACC2 -021 -085 050 092 018 -052 2579 00
ACC3 -087 041 007 064 033 -081 2219 00
ACC4 -100 027 029 067 057 -086 3169 00
ACC5 -065 001 -013 064 066 -069 1529 00
Organizational Factors
GUELP1 004 032 -024 078 -099 -075 2078 00
ATIEXICT1 019 -051 -069 089 -009 -040 1636 00
AFS1 012 -051 -044 105 -053 -036 2228 00
COMAN1 001 -017 -057 074 -018 -039 835 00
Note Positive values are indicated in bold while negative ones are not in bold
Table 5
Individual Factors per Cluster
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
AGE Most frequent
age of
students
26
Years
25
Years
25
Years
25
Years
26
Years
24
Years
356 00
GEN Most frequent
gender of
students
Male Equal
number
of male
and
female
Female Male Male Male 426 00
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 193
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
LEDUC Most frequent
year of
study of
students
Year 2 Year 2 Year 1 Year 2 Year 4 Year 1 409 00
Qualitative Analysis
Thematic analysis was used in analyzing qualitative data We used Braun and Clarke (2006)rsquos six
thematic analysis steps of familiarization generating initial codes searching reviewing defining and
naming themes and producing a report Studentsrsquo data comprised student interview data items from
which initial extracts were made Familiarization was carried out by reading and re-reading the said data
items Generating initial codes was achieved through capturing features of interest from the student data
set Searching was achieved through grouping student data relevant to potential themes Defining and
naming was achieved by categorizing the themes Finally a report about the student data was produced
The researchers used the most significant interview data that could support the quantitative results
presented in this paper in the discussion of findings section Thus the discussion of findings is
integrative
DISCUSSION OF FINDINGS
In this section qualitative findings have been integrated with the quantitative ones The letter lsquoSrsquo
denotes student Cluster 1 students were ranked third as far as the adoption of TSL is concerned because
of the quite weak alignment between the configurational factors For instance the students had no
intention to use web-based technology This was confirmed by student S5 who revealed that she did not
understand web-based learning These students could not interact with their colleagues using TSL
facilities Students in this cluster never embraced video conferencing technology because it is limited as
reflected in the main themes by the students S1 S3 and S5 However these students had the intention to
use computer technology This is consistent with student S1 who commented that ldquoI have the intention
to use computers for academic purposesrdquo They also had innovative use of TSL shown through their
ability to incorporate text audio and visual technology Furthermore these students accepted computer
technology This is supported by students S1 S2 and S6 who revealed that they use computers because
of the current education trend which demands them to be computer literate for academic purposes and
they are easy to work with
Further analysis of this cluster indicates that the organizational factors encourage these students to use
TSL facilities (see Table 4) Qualitative results from students S1 S4 and S3 respectively had the
following implications on the organizational factors
bull the goal of the TSL learning policy encourages the use of TSL facilities at a minimal level
bull students practise with ICT and also believe that the university indirectly supports them financially by
providing limited wireless fidelity
bull the university management is supportive by designing sessions on how to use computers
A typical student in this cluster was 26 years old male by gender and in his second year of study (see
Table 5) While these students have similar characteristics with those of Cluster 6 they have tried to
adopt TSL facilities compared Cluster 6 students because of their experience with such facilities
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 194
Cluster 2 students ranked second as far as adoption of TSL is concerned For example students in this
cluster revealed lsquomuchrsquo intention to use TSL For instance student S1 confirmed that ldquoWeb-based
learning offers more informationrdquo Students in this cluster were lsquovery muchrsquo capable of expounding on
what lecturers had provided to them in class using the Internet This was through ldquosurfingrdquo the Internet
using the Google search engine as revealed by student S1 Students in this cluster had lsquomuchrsquo
acceptance of TSL facilities such as web-based facilities This is because web-based learning can be
used for research work and expounding on what is taught in class by lecturers as revealed by student S1
This is confirmed by a recent study by Chopra et al (2019) that indicates that students are satisfied by
web-based technology
In relation to the organizational factors students in Cluster 2 agreed that the goal of university TSL
policy encourages their use of TSL facilities The qualitative results suggest that e-discussions can
compel students to use TSL facilities as revealed by Student S3 On average students in this cluster
were aged 25 years the number of male students was equivalent to that of female ones and they were in
their second year of study (see Table 5) These students could be better adopters than those of Cluster 1
because they seemed to have an equal gender distribution Such distribution may account for an unequal
educational technology use among Cluster 1 and 2 students who enjoyed a similar learning experience
(see Tables 4 and 5) Students of this cluster seemed to be better adopters than those of Clusters 1 3 5
and 6 because of their ability to make use of the TSL policy to their advantage (see Tables 4 and 5)
Cluster 3 students were low adopters of TSL because of low alignment between the configurational
factors thus ranked fifth as far as adoption of TSL is concerned These students lacked innovative use of
TSL facilities implying that these students cannot use such facilities to improve their learning
capabilities The same students however registered lsquovery muchrsquo acceptance of CD-ROMs (see Table 4)
This could be because this medium is a dependable way of accessing content by students (Kisanga amp
Ireson 2015)
Students in Cluster 3 perceived that the organizational factors never contributed to their use of TSL
facilities in any way (see Table 4) For example students had no time to experiment with ICT This
could be because students never practise with ICT due to the fact that the course is ldquohecticrdquo and the IT
laboratories are usually closed over the weekend as revealed by student S1 The average age gender
and level of education of a student in this cluster is 25 years female and first-year respectively (see
Table 5) These could be lower adopters of TSL than members of Clusters 2 and 5 because of their
gender Female respondents are disadvantaged when it comes to the use of information technology
(Odewumi 2018) Another plausible reason for the low adoption levels in Cluster 3 compared to those
in Clusters 2 and 1 could be the lack of innovative use of TSL (see Table 4)
Cluster 4 students were the greatest adopters of TSL among the six clusters This is because they had the
lsquogreatestrsquo alignment between the configurational factors These students are eager to use ICT innovative
and embraced TSL They are eager to use CD-ROM technology because such technology is cheap and
stores information as confirmed by students S1 and S6 They can innovatively expound on what
lectures have provided to them in class using the Internet with the help of search engines (such as
Google) as indicated by student S1 They have embraced video conference technology Students S1 S3
and S5 confirmed that they were able to imitate the limited video conferencing learning using the
WhatsApp facility
Students in Cluster 4 perceived that the organizational factors encouraged their use of TSL facilities
High scores were registered on the goal of the university TSL policy time to experiment with ICT
financial support and commitment of university management For instance during the interview process
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 195
student S3 revealed that ldquoa discussion policy for example may improve adoption of [TSL] because
once e-discussions are made they can compel one to use the [TSL] facilitiesrdquo The result from the
interview process on time to experiment with TSL conflicts with the cluster one whereby the majority
of the students never found time to practise with TSL facilities Shah and Cheng (2019) however
indicate that time influences the adoption of TSL facilities Quantitative findings in this cluster on
financial support could be related to those of student S3 who indicated that there was indirect financial
support by their university through the provision of wireless technology On the issue of management
commitment findings are in line with those of student S4 who felt that university management was
committed because they designed computer literacy sessions for them A typical student in this cluster
was 25 years old male by gender and in year 2 of study (see Table 5) This cluster (n = 42) had the
majority of the student respondents among the six clusters
The alignment of the configurational factors in Cluster 5 seemed to be lsquoweakerrsquo than that of Cluster 1
thus this cluster was ranked fourth Whereas the students in this cluster indicated lsquovery muchrsquo adoption
of TSL in some instances the configurational variables registered low scores For instance they had
very much acceptance of TSL environments yet they seemed not to be familiar with the TSL policy
The result on acceptance of TSL environments is parallel to that of Bond et al (2018) who indicated that
such environments are commonly used by students in higher education institutions in Germany The
result on the TSL policy was confirmed by student S4 who revealed that the TSL policy is not
effectively implemented in the university A normal student in this cluster was 26 years old male by
gender and in year 4 of the study (see Table 5) These students could be better adopters of TSL than
those of Clusters 3 and 6 because of their long-time experience with TSL as reflected in their year of
study compared to the said clusters (see Tables 4 and 5) It is not surprising this cluster had the best
distributions of ICTs among students
Similar to Cluster 5 Cluster 6 had 24 respondents (see Table 4) However students in this cluster are
coincidentally ranked as non-adopters of TSL among the six clusters (see Tables 4 and 5) This is
because there is no alignment between the configurational factors resulting in no adoption of TSL
These students were not willing to use IT could not modify their learning capabilities using IT and had
not realised the value of IT tools All 24 respondents in this cluster lsquoconcurredrsquo that the organization
never encouraged their use of TSL facilities This could imply that students were not involved at all
during the adoption of TSL Shah and Cheng (2019) reveal that students perceive that juggling work and
study caring for children financial difficulty and academic writing among other factors affect their
ability to adopt TSL On average students in this cluster were 26 years old male by gender and in year
1 of their study Being in their first year of study could imply that they had little experience with TSL
CONCLUSION
Identification of predictors of successful adoption of TSL among students was achieved using the
Gestalts approach Students perceived that organizational and individual factors predict successful
adoption of TSL Cluster 4 is the most coherent and as such adopted TSL most This is because the
organizational and individual factors were most aligned For example when students in this cluster are
financially supported and are in their second year of study they are eager to use to be innovative with
and embrace TSL And because of their eagerness innovativeness and ability to embrace TSL they have
accumulated more experience than others Cluster 6 students are non-adopters because they are more
inexperienced with TSL than the rest of the students
There seems to be a gap in the use of the non-linear techniques (eg clustering technique) in studies on
studentsrsquo perceptions Most studies for instance Chopra et al (2019) Gerasimova et al (2018) and Shah
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 196
and Cheng (2019) who have measured student perceptions have used linear techniques Thus this study
has closed this gap This study is a benchmark for universities in developing economies to integrate TSL
at university level For instance it should be noted that in order to achieve successful adoption of TSL
among students in universities management must be involved Nabushawo et al (2018) suggest that the
commitment of management can be achieved by collaborating with and training the users of TSL ISs
Since the world is challenged by Corona Virus Disease (COVID) this study can be used as model to
avail learning materials to students without spreading this disease
It should be noted that the rate of adoption of TSL among students is still low yet they have advanced in
age This contradicts Pereira et al (2018) who indicated that adoption of TSL usually takes place at an
early age It is therefore recommended that students should be supported to adopt TSL during their
earlier career years so that universities in Uganda can benefit from this innovation This can be done by
introducing TSL at primary level Universities need to strengthen their management capabilities such as
increasing the time studentsrsquo have to experiment with ICTs Further research is required to develop
strategies that can be adopted to enhance adoption of TSL among students at earlier ages Although this
study was carried out at a particular point in time it can also be carried out longitudinally There are
many indicators of the organization individual (student) and adoption of TSL besides those presented in
the conceptual framework Further research can be carried out on those Besides organization and
individual factors there is need to know the role of other factors in the adoption of TSL among students
While students from only two public universities were considered for this study students from other
universities can be considered as well
ACKNOWLEDGMENTS
The researchers want to thank the Almighty God for the gift of knowledge wisdom and understanding
in the writing of this paper The researchers also thank the Organization for Women in Science for the
Developing World (OWSD) and the Swedish International Development Agency (SIDA) for their
financial support in carrying out the study
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Acosta M L Sisley A Ross J Brailsford I Bhargava A Jacobs R amp Anstice N (2018) Student acceptance of e-
learning methods in the laboratory class in optometry PLOS ONE 13(12) 1-15
httpsdoiorg101371journalpone0209004
Adewole-Odeshi E (2014) Attitude of students towards e-learning in South-West Nigerian universities An application of
technology acceptance model Library Philosophy and Practice Article 1035
Angolia M G amp Pagliari L R (2016) Factors for successful evolution and sustainability of quality distance education
Online Journal of Distance Learning Administration 19(3)
Ayele B A amp Birhanie W K (2018) Acceptance and use of e-learning systems The case of teachers in technology
institutes of Ethiopian universities Applied Informatics 5(1) 1-11 httpsdoiorg101186s40535-018-0048-7
Back D A von Malotky J Sostmann K Peters H Hube R amp Hoff E (2019) Experiences with using e-learning tools
in orthopedics in an uncontrolled field study application Orthopaedics amp Traumatology Surgery amp Research
105(2) 389-393 httpsdoiorg101016jotsr201901002
Bhardwaj A amp Goundar S (2018) Students perspective of elearning and the future of education with MOOCs
International Journal of Computer Engineering 7(5) 248-260
Bhattacherjee A (2012) Social science research Principles methods and practices Textbooks Collection
httpscholarcommonsusfeduoa_textbooks3
Bond M Mariacuten V I Dolch C Bedenlier S amp Zawacki-Ritcher O (2018) Digital transformation in German higher
education Student and teacher perceptions and usage of digital media International Journal of Educational
Technology in Higher Education 15(48) httpsdoiorg101186s41239-018-0130-1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 197
Braun V amp Clarke V (2006) Using thematic analysis in psychology Qualitative Research in Psychology 33 77-101
Chopra G Madan P Jaisingh P amp Bhaskar P (2019) Effectiveness of e-learning portal from studentsrsquo perspective A
structural equation model (SEM) approach Interactive Technology and Smart Education 16(2) 94-116
httpsdoiorg101108ITSE-05-2018-0027
Creswell J W (2014) Research Design Qualitative quantitative and mixed methods approaches (4th ed) Sage
Publications
Damanpour F amp Schneider M (2006) Phases of the adoption of innovation in organisations Effects of environment
organisation and top managers British Journal of Management 17 215ndash236 httpsdoiorg101111j1467-
8551200600498x
Davis F D (1989) Perceived usefulness perceived ease of use and user acceptance of information technology MIS
Quarterly 13(3) 319ndash340 httpsdoiorg102307249008
Drazin R amp Van de Ven A H (1985) Alternative forms of fit in contingency theory Administrative Science Quarterly
30(4) 514-539 httpsdoiorg1023072392695
Drent M amp Meelissen M (2008) Which factors obstruct or stimulate teacher educators to use ICT innovatively
Computers amp Education 51 187ndash199 httpsdoiorg101016jcompedu200705001
Eze S C Chinedu-Eze V C amp Bello A O (2018) The utilisation of e-learning facilities in the educational delivery
system of Nigeria A study of M-University International Journal of Educational Technology in Higher Education
15 (34) 1-20 httpsdoiorg101186s41239-018-0116-z
Ferreira A Teixeira A L amp Dantas A R (2015) Non-technological innovation activities mediate the impacts of the
intra- and extra-organisational contexts on technological innovation outputs Enterprise and Work Innovation
Studies 11 9-43
Gerasimova V G Melamud M R Tutaeva D R Romanova Y D amp Zhenova N A (2018) The adoption of e-learning
technology at the Faculty of Distance Learning of Plekhanov Russian University of Economics Journal of Social
Studies Education Research 9(2) 172-188
Glazier R A Hamann K Pollock P H amp B Wilson B M (2019) Age gender and student success Mixing face-to-face
and online courses in political science Journal of Political Science Education 16(2) 142-157 httpsdoiorg1010801551216920181515636
Greene J C Caracelli V J amp Graham W F (1989) Toward a conceptual framework for mixed method evaluation
designs Educational Evaluation and Policy Analysis 11(3) 255-274 httpsdoiorg1023071163620
Gwamba G Renken J Nampijja J Mayende G amp Muyinda P B (2018) Contextualisation of e-learning systems in
higher education institutions In M Auer amp T Tsiatsos (Eds) Interactive mobile communication technologies and
learning Proceedings of the 11th IMCL conference (pp 44-55) Springer
Hardaker G amp Singh G (2011) The adoption and diffusion of eLearning in UK universities A comparative case study
using Giddenss theory of structuration Campus-Wide Information Systems 28(4) 221ndash233
httpsdoiorg10110810650741111162707
Kim H J Hong A J amp Song H (2019) The roles of academic engagement and digital readiness in studentsrsquo
achievements in university e-learning environments International Journal of Educational Technology in Higher
Education 16(21) 1-18 httpsdoiorg101186s41239-019-0152-3
Kimiloglu H Ozturan M amp Kutlu B (2017) Perceptions about and attitude toward the usage of e-learning in corporate
training Computers in Human Behavior 72 339-349 httpsdoiorg101016jchb201702062
Kisanga D amp Ireson G (2015) Barriers and strategies on adoption of e-learning in Tanzanian higher learning institutions
Lessons for adopters International Journal of Education and Development using Information and Communication
Technology (IJEDICT) 11(2) 126-137
Lee Y-K amp Pituch K (2002 December 10ndash13) Moderators in the adoption of e-learning An investigation of the role of
gender [Article] The Second International Conference on Electronic Business Taipei Taiwan
Lippman P C (2010) Can the physical environment have an impact on the learning environment CELE Exchange
httpsdoiorg1017875km4g21wpwr1-en
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 198
Maina M K amp Nzuki D M (2015) Adoption determinants of e-learning management system in institutions of higher
learning in Kenya A case of selected universities in Nairobi metropolitan International Journal of Business and
Social Science 6(2) 233ndash248
Martin M (1991) The culture of the telephone In PD Hopkins (Ed) Sexmachine Readings in culture gender and
technology (pp 50-74) Indiana University Press
Moakofhi M Leteane O Phiri T Pholele T amp Sebalatlheng P (2017) Challenges of introducing e-learning at
Botswana University of Agriculture and Natural Resources Lecturersrsquo perspective International Journal of
Education and Development using ICT 13( 2) 4-20
Nabushawo H M Muyinda P B Isabwe G M N Prinz A amp Mayende G (2018) Improving online interaction among
blended distance learners at Makerere University In M E Auer D Guralnick amp I Simonics (Eds) Advances in
Intelligent Systems and Computing (pp 63-69) Springer httpsdoiorg101007978-3-319-73210-7_8
Odewumi M O Yusuf M O amp Oputa G O (2018) UTAUT model Intention to use social media for learning interactive
effect of postgraduate gender in South-West Nigeria International Journal of Education and Development using
Information and Communication Technology (IJEDICT) 14(3) 239-251
Okai-Ugbaje S Ardzejewska K amp Imran A (2020) Readiness roles and responsibilities of stakeholders for sustainable
mobile learning adoption in higher education Education Sciences 10(3) 49-69
httpsdoiorg103390educsci10030049
Ozkan S amp Koseler R (2009) Multi-dimensional studentsrsquo evaluation of e-learning systems in the higher education
context An empirical investigation Computers amp Education 53(4) 1285ndash1296
httpsdoiorg101016jcompedu200906011
Parlakkılıccedil A (2014) Change management in transition to e-learning system Qualitative and Quantitative Methods in
Libraries 3(3) 637ndash651
Pereira A Martins P Morgado L amp Fonseca B (2018) Technological proposal using virtual worlds to support
entrepreneurship education for primary school children In M E Auer D Guralnick amp I Simonics (Eds)
Advances in Intelligent Systems and Computing (pp 124-132) Springer
Ramiacuterez-Correa P E Arenas-Gaitaacuten J amp Rondaacuten-Cataluntildea F J (2015) Gender and acceptance of e-learning A multi-
group analysis based on a structural equation model among college students in Chile and Spain PLOS ONE
10(10) 1-17 httpsdoiorg101371journalpone0140460
Rhema A amp Miliszewska I (2014) Analysis of student attitudes towards e-learning The case of engineering students in
Libya Issues in Informing Science and Information Technology 11 169-190 httpsdoiorg10289451987
Rogers E M (2003) Diffusion of innovations (5th ed) Free Press
Salinas J (2004) Cambios metodoloacutegicos con las TIC Estrategias didaacutecticas y entornos virtuales de ensentildeanza-aprendizaje
Bordoacuten 56(3-4) 469-481
Selim H M (2007) Critical success factors for e-learning acceptance Confirmatory factor models Computers amp
Education 49(2) 396ndash413 httpsdoi101016jcompedu200509004
Shah M amp Cheng M (2019) Exploring factors impacting student engagement in open access courses Open learning The
Journal of Open Distance and E-Learning 34(2) 187-202 httpsdoiorg1010800268051320181508337
Singh G ODonoghue J amp Worton H (2005) A study into the effects of elearning on higher education Journal of
University Teaching and Learning Practice 2(1) 13-24
Tchamyou V S (2017) The role of knowledge economy in African business Journal of the Knowledge Economy 8(4)
1189ndash1228 httpsdoiorg101007s13132-016-0417-1
The M M amp Usagawa T (2018) A comparative study of studentsrsquo readiness on e-learning education between Indonesia
and Myanmar American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS) 40(1)
113-124
Venkatraman N (1989) The concept of fit in strategy research Toward verbal and statistical correspondence Academy of
Management Review 9(3) 513-525 httpsdoiorg102307258177
Zuvic-Butorac M Nebic Z amp Nemcanin D (2011) Establishing an institutional framework for an e-learning
implementation Experiences from the University of Rijeka Croatia Journal of Information Technology Education
Innovations in Practice 10 43-56 httpsdoiorg10289451364
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Recommended Citation
-
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Cover Page Footnote
-
- tmp1624440487pdfGS9c9
-
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 185
management systems also play a vital role in the delivery of academic resources to students in
universities (Gwamba et al 2018) Bond et al (2018) indicate that LMSs are commonly used among
students in higher education institutions in Germany Nevertheless a recent study by Kim et al (2019)
indicated that students had no experience with LMSs and video technology Chopra et al (2019)
indicate that students are satisfied with web-based learning
Organizational Factors and Technology-Supported Learning
Organizational factors such as management support user training and financial incentives increase the
adoption of TSL ISs in organizations (Ayele amp Birhanie 2018) Shah and Cheng (2019) argue that
development of TSL policies is an opportunity of revolutionizing universities while engaging students
Back et al (2019) suggest that students should practice with ICTs A study by The and Usagawa (2018)
revealed that if a person practices with ICTs they gain confidence in using such tools Shah and Cheng
(2019) similarly indicate that distance learners are faced with many challenges which may force them to
drop out of universities The students cited juggling work and study caring for children financial
difficulty and academic writing among others as challenges to TSL
Another area of concern raised by Shah and Cheng (2019) was the time spent by a student studying off-
campus Such time involves experimenting with ICTs Furthermore they argue that indicators such as
online learning resources relevant course materials and building student confidence are key to positive
learning Students perceive that commitment of university management in uploading the online
resources subscribing to relevant courses and ensuring that the lecturers build confidence in them
contributes to the adoption of TSL
Students perceived that organizational support plays a vital role in their adoption of TSL (Selim 2007)
A study by Bhardwaj and Goundar (2018) reveals that students perceive that university management
does not support their use of TSL We choose to look at the goal of the TSL policy time to experiment
with ICT financial support and commitment of university management as organizational factors that
can influence studentsrsquo adoption of TSL Additionally Moakofhi et al (2017) argue that studying
organizational factors is essential in understanding technological adoption
Individual Factors and Technology-Supported Learning
Individual factors can be termed as personal factors depending on the author The individual in question
is a student Kimiloglu et al (2017) specify that individual factors can explain the adoption of TSL ISs
Parlakkılıccedil (2014) indicated that age influences the use of information technologies In addition Pereira
et al (2018) uphold that people tend to adopt TSL at an early age Gerasimova et al (2018) specified
that the average age of students who adopted TSL at the Russian University of Economics was 23 years
They revealed that the majority of these students appreciated TSL Another study by Bhardwaj and
Goundar (2018) about studentsrsquo perceptions of TSL shows that the majority of the students engaged in
the study were aged between 21 to 30 years of age
With reference to gender female students showed a preference for humanities and social sciences while
their male counterparts preferred engineering natural science and ICT (Zuvic-Butorac et al 2011)
Nevertheless Kim et al (2019) report that female students are more experienced with TSL than males
Additionally Rhema and Miliszewska (2014) revealed that there is no difference between female and
male students when it comes to the acceptance of TSL in Libyan universities Furthermore Ramiacuterez-
Correa et al (2015) studied gender behavior in relation to the studentsrsquo acceptance of TSL in Chile and
Spain Their findings revealed that there is an insignificant difference between male and female students
in the use of TSL
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 186
The year of study of a student is perceived as the level of education in this paper As per the level of
education Damanpour and Schneider (2006) revealed that education level contributes to the adoption of
innovations Technology-supported learning is perceived as something new hence an innovation
Whereas many studies have been carried out on age and gender few studies seem to focus on the
contribution of level of education to the adoption of technological innovations and less so in developing
economies
It should be noted that the definition of TSL in this paper considers the interaction between
organizational and individual factors This implies that organizational factors impact the individual
factors in relation to the adoption of TSL and vice versa
Interaction between Factors of Adoption of Technology-Supported Learning and Their Impact on Technology Supported Learning
Scholars often wonder whether the individual (student) should adapt to the organization or whether the
organization (eg university) should adapt to the individual (Lippman 2013) Lippman observes that
debatably the preceding statements are incorrect It is better to ask ldquoHow do organizations shape the
individualrdquo In turn ldquoHow does the individual impact organizationsrdquo In his argument the university
can be composed of the students other individuals and the formal physical environment Singh et al
(2005) argue that the structure of organizations has changed They indicate that TSL is part and parcel of
the organization Organizational characteristics can impact on a studentsrsquo ability to adopt TSL
Universities are usually expected to provide policies time for interaction financial support and
commitment to the students in relation to the adoption of TSL (Shah amp Cheng 2019 The amp Usagawa
2018) Students have to be in harmony with the university mission in order for the university to achieve
organizational success University TSL policy gives structure to how students should learn assess and
improve their TSL skills in a university (Makerere University Council personal communication
January nd 2004) Maina and Njuki (2015) argue that organizational TSL policies influence the
adoption of TSL The Makerere University Council (personal communication September nd 2015)
highlights that TSL policies boost pedagogical practices and improve end user skills If students are
familiar with university TSL policies chances are high that their intention innovativeness and
acceptance of TSL will be high
The time students take in interacting with ICT is an important issue in learning environments (Salinas
2004) Drent and Meelissen (2008) argued that time can be assessed according to experimenting
interacting and reflecting with ICT Time has an impact on the adoption of TSL (Shah amp Cheng 2019)
among students Developing economies have been reported to have limited e-resources which reduces
individual ability to experiment with such resources The more students experiment with ICT the more
their intention to use innovativeness and acceptance of TSL
Universities are expected to assist students through financial support to boost their adoption of TSL
(Angolia amp Pagliari 2016) They indicate that TSL comes with new support requirements Additionally
they assert that financial support enhances adoption of TSL among students in higher education
institutions They highlight that in cases where institutions often purchase TSL facilities for the students
the TSL adoption rates tend to be high
University management should be committed to supporting students to boost their adoption of TSL
(Bhardwaj amp Goundar 2018) This can be achieved through training students on how to use TSL
facilities (Kim et al 2019) Students perceive that institutional support is one of the enablers for their
adoption of TSL (Okai-Ugbaje 2020)
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 187
According to Lippman (2013) studentsrsquo age gender and level of education influence their organizations
This can be observed through variations in the use of TSL policies in place time one takes interacting
with ICTs making use of resources and also participating in activities within an organization Literature
indicates that TSL policies are common within learning institutions (Drent amp Meelissen 2008) Students
can get acquainted with these policies take time to practise with ICT use acquired TSL facilities in the
university and avail themselves to receive information from university management about TSL
Whenever a new technology is adopted it finds a society with inequalities in terms of age gender and
level of education Thus understanding the impact of age gender and level of education in the adoption
of TSL in organizations is paramount Maina and Nzuki (2015) indicate that age is an important factor in
understanding adoption of innovations in learning organizations Pereira et al (2018) indicate that
adoption of technological innovations usually takes place at an early age Adewole-Odeshi (2014)
amplifies that older people tend to have low interaction with the learning organizations resulting in low
adoption of technological innovations in such organizations
The relationship between gender and different environments has been testified (Lee amp Pituch 2002
Martin 1991) Lee and Pituch (2002) suggested that gender should not be left out in information
technology (IT ) adoption models An early study by Martin (1991) on gender differences in technology
adoption and telephone use found that womenrsquos use of the telephone for socialization purposes helped
to expand its use in both residential and business areas Odewumi et al (2018) indicate that females are
disadvantaged when it comes to the adoption of information technology
Damanpour and Schneider (2006) reveal that education level is an individual factor They continue to
argue that education is an important aspect of the adoption of innovations Maina and Nzuki (2015)
agree that level of education impacts on the learning organization during the adoption of innovations In
some instances education is viewed as a management strategy that can ease implementation of specific
innovations in particular organizations (Ferreira et al 2015) There seems to be little research on how
the level of education impacts on the learning organization during the adoption of innovations this study
acted as a basis to fill the gap A first-year student may have no knowledge of the TSL policy in a
particular learning institution which may affect their use of TSL facilities
Theoretical Underpinnings of the Study
The interactions between organizational and individual factors have been presented indicating the
complexities involved These interactions were studied with different theoretical underpinnings Factors
can be studied from a theoretical point of view that seeks to predict TSL from both organizational
(macro) and individual (micro) perspectives (Hardaker amp Singh 2011) Sometimes referred to as the
ldquoduality of structurerdquo factors can be drawn from the works of Giddens lsquotheory of structurationrsquo who
argues that macro and micro perspectives are interlinked Giddens theory is mapped to that of (Rogers
2003)rsquos Diffusion of Innovations Theory to ensure that the factors of adoption of TSL are objectively
measured For instance individual (student) was operationalized according to factors of age gender and
level of education The concept of adoption of TSL has been operationalized as intention to use
innovative use and acceptance of TSL Students can perceive that the factors encourage the adoption of
TSL or not The factors that predict successful adoption of TSL have been studied by using the
conceptual framework in Figure 1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 188
Figure 1
The Conceptual Framework of Predictors of Successful Adoption of Technology- Supported
Learning (TSL) in Universities in Uganda
Gestalts Perspective in this Study
To represent the complex interactions we have incorporated Venkatraman (1989)rsquos Gestalts fit which is
an alignment perspective Venkatraman indicates that alignment aims at balancing related organizational
components This is usually done with the aim of achieving organizational success Gestalts fit has been
achieved by configuring factors that are unique tightly integrated and fairly stable We argue that
measuring organizational and individual factors using a linear model is not appropriate Thus alignment
as Gestalts was adopted to identify those configurations of organizational and individual factors that
predict the adoption of TSL in universities
If configurational factors of the framework (ie organizational and individual factors) are well aligned
then there is greater interaction and thus an increase in the adoption of TSL On the other hand if the
elements are misaligned the level of adoption of TSL is low Thus the following hypotheses were tested
by the researchers The greater the alignment between the organizational and individual factors the more
the i) intention to use ii) innovative use and iii) acceptance of TSL in universities will be
Table 1 provides the definitions of these factors In the conceptual framework the third element is an
outcome of the interaction or interplay between the first and second variables
Table 1
Factors Constructs Employed in the Study
Factors Constructs Operationalization References
Organization Goal of TSL policy availability of time
to experiment with ICT availability of
financial support and commitment of
management
Rogers 2003 Shah amp Cheng
(2019)
Individual (student) Student age gender and level of
education
Glazier et al (2019)
Alignment
Between 1 amp 2
Organization (1) Individual
(2)
Adoption of TSL
in universities in
Uganda (3)
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 189
Factors Constructs Operationalization References
Interaction The interaction between the main factors
ie organization and the individual
affect each other
Drazine amp Van de Ven (1985)
Perception This is the studentrsquos perspective that
indicates whether the factors encourage
adoption or not
Gerasimova et al (2018)
Alignment Level of coherence Venkatraman (1989)
Adoption of TSL Intention to use innovative use and
acceptance of TSL
Rogers (2003) Davis (1989)
METHODOLOGICAL FRAMEWORK
To investigate the predictors of the successful adoption of TSL among students the quantitative survey
mixed and cross-sectional research designs were used (Creswell 2014 Greene et al 1989) A recent
study by Shah and Cheng (2019) carried out on studentsrsquo perceptions used a quantitative research
design Thus the same design was adopted for this study In quantitative designs surveys are usually
used The researchers used a survey to collect data from a total of 184 students The survey was
structured into four main parts background information adoption of TSL organizational and individual
factors Bhardwaj and Goundar (2018) in their study on studentsrsquo perceptions on TSL used a mixed
research approach The researchers adopted the said research approach whereby the largely quantitative
and little qualitative techniques were used
Besides lecturers the population of study included students from both Makerere and Gulu universities
Students were chosen because they are the main users of TSL (Bhardwaj amp Goundar 2018) and they are
faced with challenges in using this type of learning (Gerasimova et al 2018) Purposive and simple
random sampling were used for quantitative data The given universities were purposively chosen
because of the level of knowledge and use of TSL Simple random sampling was used at departmental
level to collect quantitative data from students of agricultural sciences because they are among the main
users of TSL facilities at this level Purposive homogeneous sampling was used for qualitative data A
total of six students were interviewed to complement the questionnaire data
The study took place at a particular point in time hence it was cross-sectional in nature Internal and
external validity checks were used (Bhattacherjee 2012) Internal validity was achieved by omitting
extraneous variables so that changes in the response to variables is caused by the hypothesized
explanatory variables External validity was achieved by generalizing from Makerere and Gulu
universities to other universities These two universities were chosen because their lecturers have been
motivated earlier their students would have had more exposure to the technology adoption and with that
experience it would be appropriate to capture their perspectives Validity of the student qualitative
instrument was achieved through use of research experts who were used to validate whether the content
in the instrument could get the data required (Ozkan amp Koseler 2009)
Additionally the developed question concepts were derived from past relevant studies This can be
related to Bhardwaj and Goundar (2019) who captured studentsrsquo perceptions on TSL based on the
modification of concepts from relevant past studies Studies on studentsrsquo perceptions taking a
quantitative approach are usually carried out using reliability tests Kim et al (2019) carried out a
reliability test on a questionnaire that was administered to undergraduate students in a university in
Korea using Cronbachrsquos alpha Similarly the researchers used the same alpha to test questions in the
student self-administered questionnaire The outcome variable of the adoption of TSL was
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 190
operationalized as intention to use innovative use and acceptance of TSL with Cronbach alphas of 064
067 070 respectively The organizational factors had a Cronbach alpha of 073 The researchers
followed ethics guidelines to accomplish the study
RESULTS AND ANALYSIS
Background Information
The majority (821) of the students were aged between 21 and 30 years old This is in line with
Bhardwaj and Goundar (2018) who indicated that the majority of the student respondents were between
21 to 30 years old The majority (641) of the student respondents were male while 359 were female
respondents This is in line with Zuvic-Butorac et al (2011) who found that female students
concentrated on art subjects while their male counterparts were in engineering natural science and ICT
Most (410) of the students were in their second year of study followed by first year students (ie
320) The majority of the students (ie 940) had access to email Few (386) students had laptops
This is because these students may not be in position to afford such devices Most (592) of the
respondents revealed that there are functional TSL laboratories in their universities Most of the students
(571) were affiliated to Gulu University For descriptive analysis of means and standard deviations
for selected research variables see Tables 2 and 3 All the data simulations were based on a Likert scale
of 5 Descriptive analysis of the individual (student) presenting modal age gender and level of education
of the whole population of students (ie N =184) is shown in Table 3
Descriptive Statistics
Table 2
Descriptive Statistics for Selected Research Variables (N =184)
Variable Brief Description of Variables M a Min Max SD
Adoption of TSL
Intention to Use
ITU1 Computers 445 1 5 0979
ITU2 CD-ROMs 283 1 5 1468
ITU3 Web-based learning 384 1 5 1344
ITU4 Video conferencing 359 1 5 1449
ITU5 University TSL environments eg Black-Board 366 1 5 1425
Innovative Use
INU1 I am able to expound on what lecturers have provided to me in class using
the Internet
379 1 5 1334
INU2 I am able to make presentations in text audio and visual 380 1 5 1424
INU3 I am able to communicate with other students through online discussions
emails wikis and WhatsApp
371 1 5 1496
Acceptance
ACC1 Computers 452 1 5 0941
ACC2 CD-ROMs 296 1 5 1536
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 191
Variable Brief Description of Variables M a Min Max SD
ACC3 Web-based learning 375 1 5 1388
ACC4 Video conferencing 359 1 5 1376
ACC5 University TSL environments eg Black-Board 361 1 5 1536
Organizational Factors
GUELP1 Goal of university TSL policy 297 1 5 1408
ATIEXICT1 Availability of time to experiment with ICT 322 1 5 1366
AFS1 Availability of financial support 273 1 5 1544
COMAN1 Commitment of management 304 1 5 1362
a A score of 350 indicates that the person has and there was ldquoeg intention to use TSL encouragement
on use of TSL facilities and ldquohindrance to the progress of TSL ISsrdquo on the five-point Likert scale of
1(Very little or no intention to use TSL encouragement on use of TSL facilities and hindrance to the
progress of TSL ISs ) and 5(Very much intention to use TSL greatest encouragement on use of TSL
facilities and very much hindrance to the progress of TSL ISs)
Students had lsquomuchrsquo intention to use TSL facilities For instance they had lsquomuchrsquo intention to use
computers (ITU1) The students had lsquomuchrsquo innovative use of TSL (for instance they were able to make
presentations in text audio and video INU2) They also indicated very much acceptance of TSL For
instance they had very much acceptance of computers (ACC1)
See Table 3 for most frequent characteristics of each individual in the whole student population (ie N
=184)
Table 3
Individual Factors (N = 184)
Individual Factors Rate of Occurrence Most Frequent
Individual Factors
AGE Most frequent age of students 25 Years
GEN Most frequent gender of students Male
LEDUC Most frequent year of study of students Year 2
Cluster Analyses
The researchers used the k-means clustering algorithm with the help of Statistica Software version 133
to generate six clusters The data were standardized Whereas several simulations were carried out (ie1
2 3 4 5 and 6) only the sixth simulation showed acceptable results All 6 simulations yielded p values
less than 005 (see Table 4) Table 4 indicates the measurement of the organizational factors and
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 192
adoption of TSL in universities in Uganda across the six student clusters Table 5 shows the
measurement of the individual factors across the said clusters
Table 4
Cluster Analysis and Analysis of Variance for Students
Cluster
Variable 1
(n = 37)
2
(n = 38)
3
(n = 19)
4
(n = 42)
5
(n = 24)
6
(n = 24)
ANOVA
F p
Adoption of TSL
Intention to Use TSL
ITU1 011 024 002 032 048 -161 244 00
ITU2 -007 -074 033 069 -014 -005 1109 00
ITU3 -101 037 035 058 039 -072 2502 00
ITU4 -084 031 031 059 031 -079 1893 00
ITU5 -056 022 -006 059 029 -078 1159 00
Innovative Use of TSL
INU1 -025 051 -024 065 -013 -122 2075 00
INU2 014 029 -142 049 052 -092 2671 00
INU3 -051 044 -128 061 049 -045 2449 00
Acceptance of TSL
ACC1 023 023 007 039 034 -179 3439 00
ACC2 -021 -085 050 092 018 -052 2579 00
ACC3 -087 041 007 064 033 -081 2219 00
ACC4 -100 027 029 067 057 -086 3169 00
ACC5 -065 001 -013 064 066 -069 1529 00
Organizational Factors
GUELP1 004 032 -024 078 -099 -075 2078 00
ATIEXICT1 019 -051 -069 089 -009 -040 1636 00
AFS1 012 -051 -044 105 -053 -036 2228 00
COMAN1 001 -017 -057 074 -018 -039 835 00
Note Positive values are indicated in bold while negative ones are not in bold
Table 5
Individual Factors per Cluster
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
AGE Most frequent
age of
students
26
Years
25
Years
25
Years
25
Years
26
Years
24
Years
356 00
GEN Most frequent
gender of
students
Male Equal
number
of male
and
female
Female Male Male Male 426 00
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 193
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
LEDUC Most frequent
year of
study of
students
Year 2 Year 2 Year 1 Year 2 Year 4 Year 1 409 00
Qualitative Analysis
Thematic analysis was used in analyzing qualitative data We used Braun and Clarke (2006)rsquos six
thematic analysis steps of familiarization generating initial codes searching reviewing defining and
naming themes and producing a report Studentsrsquo data comprised student interview data items from
which initial extracts were made Familiarization was carried out by reading and re-reading the said data
items Generating initial codes was achieved through capturing features of interest from the student data
set Searching was achieved through grouping student data relevant to potential themes Defining and
naming was achieved by categorizing the themes Finally a report about the student data was produced
The researchers used the most significant interview data that could support the quantitative results
presented in this paper in the discussion of findings section Thus the discussion of findings is
integrative
DISCUSSION OF FINDINGS
In this section qualitative findings have been integrated with the quantitative ones The letter lsquoSrsquo
denotes student Cluster 1 students were ranked third as far as the adoption of TSL is concerned because
of the quite weak alignment between the configurational factors For instance the students had no
intention to use web-based technology This was confirmed by student S5 who revealed that she did not
understand web-based learning These students could not interact with their colleagues using TSL
facilities Students in this cluster never embraced video conferencing technology because it is limited as
reflected in the main themes by the students S1 S3 and S5 However these students had the intention to
use computer technology This is consistent with student S1 who commented that ldquoI have the intention
to use computers for academic purposesrdquo They also had innovative use of TSL shown through their
ability to incorporate text audio and visual technology Furthermore these students accepted computer
technology This is supported by students S1 S2 and S6 who revealed that they use computers because
of the current education trend which demands them to be computer literate for academic purposes and
they are easy to work with
Further analysis of this cluster indicates that the organizational factors encourage these students to use
TSL facilities (see Table 4) Qualitative results from students S1 S4 and S3 respectively had the
following implications on the organizational factors
bull the goal of the TSL learning policy encourages the use of TSL facilities at a minimal level
bull students practise with ICT and also believe that the university indirectly supports them financially by
providing limited wireless fidelity
bull the university management is supportive by designing sessions on how to use computers
A typical student in this cluster was 26 years old male by gender and in his second year of study (see
Table 5) While these students have similar characteristics with those of Cluster 6 they have tried to
adopt TSL facilities compared Cluster 6 students because of their experience with such facilities
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 194
Cluster 2 students ranked second as far as adoption of TSL is concerned For example students in this
cluster revealed lsquomuchrsquo intention to use TSL For instance student S1 confirmed that ldquoWeb-based
learning offers more informationrdquo Students in this cluster were lsquovery muchrsquo capable of expounding on
what lecturers had provided to them in class using the Internet This was through ldquosurfingrdquo the Internet
using the Google search engine as revealed by student S1 Students in this cluster had lsquomuchrsquo
acceptance of TSL facilities such as web-based facilities This is because web-based learning can be
used for research work and expounding on what is taught in class by lecturers as revealed by student S1
This is confirmed by a recent study by Chopra et al (2019) that indicates that students are satisfied by
web-based technology
In relation to the organizational factors students in Cluster 2 agreed that the goal of university TSL
policy encourages their use of TSL facilities The qualitative results suggest that e-discussions can
compel students to use TSL facilities as revealed by Student S3 On average students in this cluster
were aged 25 years the number of male students was equivalent to that of female ones and they were in
their second year of study (see Table 5) These students could be better adopters than those of Cluster 1
because they seemed to have an equal gender distribution Such distribution may account for an unequal
educational technology use among Cluster 1 and 2 students who enjoyed a similar learning experience
(see Tables 4 and 5) Students of this cluster seemed to be better adopters than those of Clusters 1 3 5
and 6 because of their ability to make use of the TSL policy to their advantage (see Tables 4 and 5)
Cluster 3 students were low adopters of TSL because of low alignment between the configurational
factors thus ranked fifth as far as adoption of TSL is concerned These students lacked innovative use of
TSL facilities implying that these students cannot use such facilities to improve their learning
capabilities The same students however registered lsquovery muchrsquo acceptance of CD-ROMs (see Table 4)
This could be because this medium is a dependable way of accessing content by students (Kisanga amp
Ireson 2015)
Students in Cluster 3 perceived that the organizational factors never contributed to their use of TSL
facilities in any way (see Table 4) For example students had no time to experiment with ICT This
could be because students never practise with ICT due to the fact that the course is ldquohecticrdquo and the IT
laboratories are usually closed over the weekend as revealed by student S1 The average age gender
and level of education of a student in this cluster is 25 years female and first-year respectively (see
Table 5) These could be lower adopters of TSL than members of Clusters 2 and 5 because of their
gender Female respondents are disadvantaged when it comes to the use of information technology
(Odewumi 2018) Another plausible reason for the low adoption levels in Cluster 3 compared to those
in Clusters 2 and 1 could be the lack of innovative use of TSL (see Table 4)
Cluster 4 students were the greatest adopters of TSL among the six clusters This is because they had the
lsquogreatestrsquo alignment between the configurational factors These students are eager to use ICT innovative
and embraced TSL They are eager to use CD-ROM technology because such technology is cheap and
stores information as confirmed by students S1 and S6 They can innovatively expound on what
lectures have provided to them in class using the Internet with the help of search engines (such as
Google) as indicated by student S1 They have embraced video conference technology Students S1 S3
and S5 confirmed that they were able to imitate the limited video conferencing learning using the
WhatsApp facility
Students in Cluster 4 perceived that the organizational factors encouraged their use of TSL facilities
High scores were registered on the goal of the university TSL policy time to experiment with ICT
financial support and commitment of university management For instance during the interview process
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 195
student S3 revealed that ldquoa discussion policy for example may improve adoption of [TSL] because
once e-discussions are made they can compel one to use the [TSL] facilitiesrdquo The result from the
interview process on time to experiment with TSL conflicts with the cluster one whereby the majority
of the students never found time to practise with TSL facilities Shah and Cheng (2019) however
indicate that time influences the adoption of TSL facilities Quantitative findings in this cluster on
financial support could be related to those of student S3 who indicated that there was indirect financial
support by their university through the provision of wireless technology On the issue of management
commitment findings are in line with those of student S4 who felt that university management was
committed because they designed computer literacy sessions for them A typical student in this cluster
was 25 years old male by gender and in year 2 of study (see Table 5) This cluster (n = 42) had the
majority of the student respondents among the six clusters
The alignment of the configurational factors in Cluster 5 seemed to be lsquoweakerrsquo than that of Cluster 1
thus this cluster was ranked fourth Whereas the students in this cluster indicated lsquovery muchrsquo adoption
of TSL in some instances the configurational variables registered low scores For instance they had
very much acceptance of TSL environments yet they seemed not to be familiar with the TSL policy
The result on acceptance of TSL environments is parallel to that of Bond et al (2018) who indicated that
such environments are commonly used by students in higher education institutions in Germany The
result on the TSL policy was confirmed by student S4 who revealed that the TSL policy is not
effectively implemented in the university A normal student in this cluster was 26 years old male by
gender and in year 4 of the study (see Table 5) These students could be better adopters of TSL than
those of Clusters 3 and 6 because of their long-time experience with TSL as reflected in their year of
study compared to the said clusters (see Tables 4 and 5) It is not surprising this cluster had the best
distributions of ICTs among students
Similar to Cluster 5 Cluster 6 had 24 respondents (see Table 4) However students in this cluster are
coincidentally ranked as non-adopters of TSL among the six clusters (see Tables 4 and 5) This is
because there is no alignment between the configurational factors resulting in no adoption of TSL
These students were not willing to use IT could not modify their learning capabilities using IT and had
not realised the value of IT tools All 24 respondents in this cluster lsquoconcurredrsquo that the organization
never encouraged their use of TSL facilities This could imply that students were not involved at all
during the adoption of TSL Shah and Cheng (2019) reveal that students perceive that juggling work and
study caring for children financial difficulty and academic writing among other factors affect their
ability to adopt TSL On average students in this cluster were 26 years old male by gender and in year
1 of their study Being in their first year of study could imply that they had little experience with TSL
CONCLUSION
Identification of predictors of successful adoption of TSL among students was achieved using the
Gestalts approach Students perceived that organizational and individual factors predict successful
adoption of TSL Cluster 4 is the most coherent and as such adopted TSL most This is because the
organizational and individual factors were most aligned For example when students in this cluster are
financially supported and are in their second year of study they are eager to use to be innovative with
and embrace TSL And because of their eagerness innovativeness and ability to embrace TSL they have
accumulated more experience than others Cluster 6 students are non-adopters because they are more
inexperienced with TSL than the rest of the students
There seems to be a gap in the use of the non-linear techniques (eg clustering technique) in studies on
studentsrsquo perceptions Most studies for instance Chopra et al (2019) Gerasimova et al (2018) and Shah
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 196
and Cheng (2019) who have measured student perceptions have used linear techniques Thus this study
has closed this gap This study is a benchmark for universities in developing economies to integrate TSL
at university level For instance it should be noted that in order to achieve successful adoption of TSL
among students in universities management must be involved Nabushawo et al (2018) suggest that the
commitment of management can be achieved by collaborating with and training the users of TSL ISs
Since the world is challenged by Corona Virus Disease (COVID) this study can be used as model to
avail learning materials to students without spreading this disease
It should be noted that the rate of adoption of TSL among students is still low yet they have advanced in
age This contradicts Pereira et al (2018) who indicated that adoption of TSL usually takes place at an
early age It is therefore recommended that students should be supported to adopt TSL during their
earlier career years so that universities in Uganda can benefit from this innovation This can be done by
introducing TSL at primary level Universities need to strengthen their management capabilities such as
increasing the time studentsrsquo have to experiment with ICTs Further research is required to develop
strategies that can be adopted to enhance adoption of TSL among students at earlier ages Although this
study was carried out at a particular point in time it can also be carried out longitudinally There are
many indicators of the organization individual (student) and adoption of TSL besides those presented in
the conceptual framework Further research can be carried out on those Besides organization and
individual factors there is need to know the role of other factors in the adoption of TSL among students
While students from only two public universities were considered for this study students from other
universities can be considered as well
ACKNOWLEDGMENTS
The researchers want to thank the Almighty God for the gift of knowledge wisdom and understanding
in the writing of this paper The researchers also thank the Organization for Women in Science for the
Developing World (OWSD) and the Swedish International Development Agency (SIDA) for their
financial support in carrying out the study
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Acosta M L Sisley A Ross J Brailsford I Bhargava A Jacobs R amp Anstice N (2018) Student acceptance of e-
learning methods in the laboratory class in optometry PLOS ONE 13(12) 1-15
httpsdoiorg101371journalpone0209004
Adewole-Odeshi E (2014) Attitude of students towards e-learning in South-West Nigerian universities An application of
technology acceptance model Library Philosophy and Practice Article 1035
Angolia M G amp Pagliari L R (2016) Factors for successful evolution and sustainability of quality distance education
Online Journal of Distance Learning Administration 19(3)
Ayele B A amp Birhanie W K (2018) Acceptance and use of e-learning systems The case of teachers in technology
institutes of Ethiopian universities Applied Informatics 5(1) 1-11 httpsdoiorg101186s40535-018-0048-7
Back D A von Malotky J Sostmann K Peters H Hube R amp Hoff E (2019) Experiences with using e-learning tools
in orthopedics in an uncontrolled field study application Orthopaedics amp Traumatology Surgery amp Research
105(2) 389-393 httpsdoiorg101016jotsr201901002
Bhardwaj A amp Goundar S (2018) Students perspective of elearning and the future of education with MOOCs
International Journal of Computer Engineering 7(5) 248-260
Bhattacherjee A (2012) Social science research Principles methods and practices Textbooks Collection
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Bond M Mariacuten V I Dolch C Bedenlier S amp Zawacki-Ritcher O (2018) Digital transformation in German higher
education Student and teacher perceptions and usage of digital media International Journal of Educational
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Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 197
Braun V amp Clarke V (2006) Using thematic analysis in psychology Qualitative Research in Psychology 33 77-101
Chopra G Madan P Jaisingh P amp Bhaskar P (2019) Effectiveness of e-learning portal from studentsrsquo perspective A
structural equation model (SEM) approach Interactive Technology and Smart Education 16(2) 94-116
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Creswell J W (2014) Research Design Qualitative quantitative and mixed methods approaches (4th ed) Sage
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Damanpour F amp Schneider M (2006) Phases of the adoption of innovation in organisations Effects of environment
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Davis F D (1989) Perceived usefulness perceived ease of use and user acceptance of information technology MIS
Quarterly 13(3) 319ndash340 httpsdoiorg102307249008
Drazin R amp Van de Ven A H (1985) Alternative forms of fit in contingency theory Administrative Science Quarterly
30(4) 514-539 httpsdoiorg1023072392695
Drent M amp Meelissen M (2008) Which factors obstruct or stimulate teacher educators to use ICT innovatively
Computers amp Education 51 187ndash199 httpsdoiorg101016jcompedu200705001
Eze S C Chinedu-Eze V C amp Bello A O (2018) The utilisation of e-learning facilities in the educational delivery
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Ferreira A Teixeira A L amp Dantas A R (2015) Non-technological innovation activities mediate the impacts of the
intra- and extra-organisational contexts on technological innovation outputs Enterprise and Work Innovation
Studies 11 9-43
Gerasimova V G Melamud M R Tutaeva D R Romanova Y D amp Zhenova N A (2018) The adoption of e-learning
technology at the Faculty of Distance Learning of Plekhanov Russian University of Economics Journal of Social
Studies Education Research 9(2) 172-188
Glazier R A Hamann K Pollock P H amp B Wilson B M (2019) Age gender and student success Mixing face-to-face
and online courses in political science Journal of Political Science Education 16(2) 142-157 httpsdoiorg1010801551216920181515636
Greene J C Caracelli V J amp Graham W F (1989) Toward a conceptual framework for mixed method evaluation
designs Educational Evaluation and Policy Analysis 11(3) 255-274 httpsdoiorg1023071163620
Gwamba G Renken J Nampijja J Mayende G amp Muyinda P B (2018) Contextualisation of e-learning systems in
higher education institutions In M Auer amp T Tsiatsos (Eds) Interactive mobile communication technologies and
learning Proceedings of the 11th IMCL conference (pp 44-55) Springer
Hardaker G amp Singh G (2011) The adoption and diffusion of eLearning in UK universities A comparative case study
using Giddenss theory of structuration Campus-Wide Information Systems 28(4) 221ndash233
httpsdoiorg10110810650741111162707
Kim H J Hong A J amp Song H (2019) The roles of academic engagement and digital readiness in studentsrsquo
achievements in university e-learning environments International Journal of Educational Technology in Higher
Education 16(21) 1-18 httpsdoiorg101186s41239-019-0152-3
Kimiloglu H Ozturan M amp Kutlu B (2017) Perceptions about and attitude toward the usage of e-learning in corporate
training Computers in Human Behavior 72 339-349 httpsdoiorg101016jchb201702062
Kisanga D amp Ireson G (2015) Barriers and strategies on adoption of e-learning in Tanzanian higher learning institutions
Lessons for adopters International Journal of Education and Development using Information and Communication
Technology (IJEDICT) 11(2) 126-137
Lee Y-K amp Pituch K (2002 December 10ndash13) Moderators in the adoption of e-learning An investigation of the role of
gender [Article] The Second International Conference on Electronic Business Taipei Taiwan
Lippman P C (2010) Can the physical environment have an impact on the learning environment CELE Exchange
httpsdoiorg1017875km4g21wpwr1-en
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 198
Maina M K amp Nzuki D M (2015) Adoption determinants of e-learning management system in institutions of higher
learning in Kenya A case of selected universities in Nairobi metropolitan International Journal of Business and
Social Science 6(2) 233ndash248
Martin M (1991) The culture of the telephone In PD Hopkins (Ed) Sexmachine Readings in culture gender and
technology (pp 50-74) Indiana University Press
Moakofhi M Leteane O Phiri T Pholele T amp Sebalatlheng P (2017) Challenges of introducing e-learning at
Botswana University of Agriculture and Natural Resources Lecturersrsquo perspective International Journal of
Education and Development using ICT 13( 2) 4-20
Nabushawo H M Muyinda P B Isabwe G M N Prinz A amp Mayende G (2018) Improving online interaction among
blended distance learners at Makerere University In M E Auer D Guralnick amp I Simonics (Eds) Advances in
Intelligent Systems and Computing (pp 63-69) Springer httpsdoiorg101007978-3-319-73210-7_8
Odewumi M O Yusuf M O amp Oputa G O (2018) UTAUT model Intention to use social media for learning interactive
effect of postgraduate gender in South-West Nigeria International Journal of Education and Development using
Information and Communication Technology (IJEDICT) 14(3) 239-251
Okai-Ugbaje S Ardzejewska K amp Imran A (2020) Readiness roles and responsibilities of stakeholders for sustainable
mobile learning adoption in higher education Education Sciences 10(3) 49-69
httpsdoiorg103390educsci10030049
Ozkan S amp Koseler R (2009) Multi-dimensional studentsrsquo evaluation of e-learning systems in the higher education
context An empirical investigation Computers amp Education 53(4) 1285ndash1296
httpsdoiorg101016jcompedu200906011
Parlakkılıccedil A (2014) Change management in transition to e-learning system Qualitative and Quantitative Methods in
Libraries 3(3) 637ndash651
Pereira A Martins P Morgado L amp Fonseca B (2018) Technological proposal using virtual worlds to support
entrepreneurship education for primary school children In M E Auer D Guralnick amp I Simonics (Eds)
Advances in Intelligent Systems and Computing (pp 124-132) Springer
Ramiacuterez-Correa P E Arenas-Gaitaacuten J amp Rondaacuten-Cataluntildea F J (2015) Gender and acceptance of e-learning A multi-
group analysis based on a structural equation model among college students in Chile and Spain PLOS ONE
10(10) 1-17 httpsdoiorg101371journalpone0140460
Rhema A amp Miliszewska I (2014) Analysis of student attitudes towards e-learning The case of engineering students in
Libya Issues in Informing Science and Information Technology 11 169-190 httpsdoiorg10289451987
Rogers E M (2003) Diffusion of innovations (5th ed) Free Press
Salinas J (2004) Cambios metodoloacutegicos con las TIC Estrategias didaacutecticas y entornos virtuales de ensentildeanza-aprendizaje
Bordoacuten 56(3-4) 469-481
Selim H M (2007) Critical success factors for e-learning acceptance Confirmatory factor models Computers amp
Education 49(2) 396ndash413 httpsdoi101016jcompedu200509004
Shah M amp Cheng M (2019) Exploring factors impacting student engagement in open access courses Open learning The
Journal of Open Distance and E-Learning 34(2) 187-202 httpsdoiorg1010800268051320181508337
Singh G ODonoghue J amp Worton H (2005) A study into the effects of elearning on higher education Journal of
University Teaching and Learning Practice 2(1) 13-24
Tchamyou V S (2017) The role of knowledge economy in African business Journal of the Knowledge Economy 8(4)
1189ndash1228 httpsdoiorg101007s13132-016-0417-1
The M M amp Usagawa T (2018) A comparative study of studentsrsquo readiness on e-learning education between Indonesia
and Myanmar American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS) 40(1)
113-124
Venkatraman N (1989) The concept of fit in strategy research Toward verbal and statistical correspondence Academy of
Management Review 9(3) 513-525 httpsdoiorg102307258177
Zuvic-Butorac M Nebic Z amp Nemcanin D (2011) Establishing an institutional framework for an e-learning
implementation Experiences from the University of Rijeka Croatia Journal of Information Technology Education
Innovations in Practice 10 43-56 httpsdoiorg10289451364
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Recommended Citation
-
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Cover Page Footnote
-
- tmp1624440487pdfGS9c9
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Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 186
The year of study of a student is perceived as the level of education in this paper As per the level of
education Damanpour and Schneider (2006) revealed that education level contributes to the adoption of
innovations Technology-supported learning is perceived as something new hence an innovation
Whereas many studies have been carried out on age and gender few studies seem to focus on the
contribution of level of education to the adoption of technological innovations and less so in developing
economies
It should be noted that the definition of TSL in this paper considers the interaction between
organizational and individual factors This implies that organizational factors impact the individual
factors in relation to the adoption of TSL and vice versa
Interaction between Factors of Adoption of Technology-Supported Learning and Their Impact on Technology Supported Learning
Scholars often wonder whether the individual (student) should adapt to the organization or whether the
organization (eg university) should adapt to the individual (Lippman 2013) Lippman observes that
debatably the preceding statements are incorrect It is better to ask ldquoHow do organizations shape the
individualrdquo In turn ldquoHow does the individual impact organizationsrdquo In his argument the university
can be composed of the students other individuals and the formal physical environment Singh et al
(2005) argue that the structure of organizations has changed They indicate that TSL is part and parcel of
the organization Organizational characteristics can impact on a studentsrsquo ability to adopt TSL
Universities are usually expected to provide policies time for interaction financial support and
commitment to the students in relation to the adoption of TSL (Shah amp Cheng 2019 The amp Usagawa
2018) Students have to be in harmony with the university mission in order for the university to achieve
organizational success University TSL policy gives structure to how students should learn assess and
improve their TSL skills in a university (Makerere University Council personal communication
January nd 2004) Maina and Njuki (2015) argue that organizational TSL policies influence the
adoption of TSL The Makerere University Council (personal communication September nd 2015)
highlights that TSL policies boost pedagogical practices and improve end user skills If students are
familiar with university TSL policies chances are high that their intention innovativeness and
acceptance of TSL will be high
The time students take in interacting with ICT is an important issue in learning environments (Salinas
2004) Drent and Meelissen (2008) argued that time can be assessed according to experimenting
interacting and reflecting with ICT Time has an impact on the adoption of TSL (Shah amp Cheng 2019)
among students Developing economies have been reported to have limited e-resources which reduces
individual ability to experiment with such resources The more students experiment with ICT the more
their intention to use innovativeness and acceptance of TSL
Universities are expected to assist students through financial support to boost their adoption of TSL
(Angolia amp Pagliari 2016) They indicate that TSL comes with new support requirements Additionally
they assert that financial support enhances adoption of TSL among students in higher education
institutions They highlight that in cases where institutions often purchase TSL facilities for the students
the TSL adoption rates tend to be high
University management should be committed to supporting students to boost their adoption of TSL
(Bhardwaj amp Goundar 2018) This can be achieved through training students on how to use TSL
facilities (Kim et al 2019) Students perceive that institutional support is one of the enablers for their
adoption of TSL (Okai-Ugbaje 2020)
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 187
According to Lippman (2013) studentsrsquo age gender and level of education influence their organizations
This can be observed through variations in the use of TSL policies in place time one takes interacting
with ICTs making use of resources and also participating in activities within an organization Literature
indicates that TSL policies are common within learning institutions (Drent amp Meelissen 2008) Students
can get acquainted with these policies take time to practise with ICT use acquired TSL facilities in the
university and avail themselves to receive information from university management about TSL
Whenever a new technology is adopted it finds a society with inequalities in terms of age gender and
level of education Thus understanding the impact of age gender and level of education in the adoption
of TSL in organizations is paramount Maina and Nzuki (2015) indicate that age is an important factor in
understanding adoption of innovations in learning organizations Pereira et al (2018) indicate that
adoption of technological innovations usually takes place at an early age Adewole-Odeshi (2014)
amplifies that older people tend to have low interaction with the learning organizations resulting in low
adoption of technological innovations in such organizations
The relationship between gender and different environments has been testified (Lee amp Pituch 2002
Martin 1991) Lee and Pituch (2002) suggested that gender should not be left out in information
technology (IT ) adoption models An early study by Martin (1991) on gender differences in technology
adoption and telephone use found that womenrsquos use of the telephone for socialization purposes helped
to expand its use in both residential and business areas Odewumi et al (2018) indicate that females are
disadvantaged when it comes to the adoption of information technology
Damanpour and Schneider (2006) reveal that education level is an individual factor They continue to
argue that education is an important aspect of the adoption of innovations Maina and Nzuki (2015)
agree that level of education impacts on the learning organization during the adoption of innovations In
some instances education is viewed as a management strategy that can ease implementation of specific
innovations in particular organizations (Ferreira et al 2015) There seems to be little research on how
the level of education impacts on the learning organization during the adoption of innovations this study
acted as a basis to fill the gap A first-year student may have no knowledge of the TSL policy in a
particular learning institution which may affect their use of TSL facilities
Theoretical Underpinnings of the Study
The interactions between organizational and individual factors have been presented indicating the
complexities involved These interactions were studied with different theoretical underpinnings Factors
can be studied from a theoretical point of view that seeks to predict TSL from both organizational
(macro) and individual (micro) perspectives (Hardaker amp Singh 2011) Sometimes referred to as the
ldquoduality of structurerdquo factors can be drawn from the works of Giddens lsquotheory of structurationrsquo who
argues that macro and micro perspectives are interlinked Giddens theory is mapped to that of (Rogers
2003)rsquos Diffusion of Innovations Theory to ensure that the factors of adoption of TSL are objectively
measured For instance individual (student) was operationalized according to factors of age gender and
level of education The concept of adoption of TSL has been operationalized as intention to use
innovative use and acceptance of TSL Students can perceive that the factors encourage the adoption of
TSL or not The factors that predict successful adoption of TSL have been studied by using the
conceptual framework in Figure 1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 188
Figure 1
The Conceptual Framework of Predictors of Successful Adoption of Technology- Supported
Learning (TSL) in Universities in Uganda
Gestalts Perspective in this Study
To represent the complex interactions we have incorporated Venkatraman (1989)rsquos Gestalts fit which is
an alignment perspective Venkatraman indicates that alignment aims at balancing related organizational
components This is usually done with the aim of achieving organizational success Gestalts fit has been
achieved by configuring factors that are unique tightly integrated and fairly stable We argue that
measuring organizational and individual factors using a linear model is not appropriate Thus alignment
as Gestalts was adopted to identify those configurations of organizational and individual factors that
predict the adoption of TSL in universities
If configurational factors of the framework (ie organizational and individual factors) are well aligned
then there is greater interaction and thus an increase in the adoption of TSL On the other hand if the
elements are misaligned the level of adoption of TSL is low Thus the following hypotheses were tested
by the researchers The greater the alignment between the organizational and individual factors the more
the i) intention to use ii) innovative use and iii) acceptance of TSL in universities will be
Table 1 provides the definitions of these factors In the conceptual framework the third element is an
outcome of the interaction or interplay between the first and second variables
Table 1
Factors Constructs Employed in the Study
Factors Constructs Operationalization References
Organization Goal of TSL policy availability of time
to experiment with ICT availability of
financial support and commitment of
management
Rogers 2003 Shah amp Cheng
(2019)
Individual (student) Student age gender and level of
education
Glazier et al (2019)
Alignment
Between 1 amp 2
Organization (1) Individual
(2)
Adoption of TSL
in universities in
Uganda (3)
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 189
Factors Constructs Operationalization References
Interaction The interaction between the main factors
ie organization and the individual
affect each other
Drazine amp Van de Ven (1985)
Perception This is the studentrsquos perspective that
indicates whether the factors encourage
adoption or not
Gerasimova et al (2018)
Alignment Level of coherence Venkatraman (1989)
Adoption of TSL Intention to use innovative use and
acceptance of TSL
Rogers (2003) Davis (1989)
METHODOLOGICAL FRAMEWORK
To investigate the predictors of the successful adoption of TSL among students the quantitative survey
mixed and cross-sectional research designs were used (Creswell 2014 Greene et al 1989) A recent
study by Shah and Cheng (2019) carried out on studentsrsquo perceptions used a quantitative research
design Thus the same design was adopted for this study In quantitative designs surveys are usually
used The researchers used a survey to collect data from a total of 184 students The survey was
structured into four main parts background information adoption of TSL organizational and individual
factors Bhardwaj and Goundar (2018) in their study on studentsrsquo perceptions on TSL used a mixed
research approach The researchers adopted the said research approach whereby the largely quantitative
and little qualitative techniques were used
Besides lecturers the population of study included students from both Makerere and Gulu universities
Students were chosen because they are the main users of TSL (Bhardwaj amp Goundar 2018) and they are
faced with challenges in using this type of learning (Gerasimova et al 2018) Purposive and simple
random sampling were used for quantitative data The given universities were purposively chosen
because of the level of knowledge and use of TSL Simple random sampling was used at departmental
level to collect quantitative data from students of agricultural sciences because they are among the main
users of TSL facilities at this level Purposive homogeneous sampling was used for qualitative data A
total of six students were interviewed to complement the questionnaire data
The study took place at a particular point in time hence it was cross-sectional in nature Internal and
external validity checks were used (Bhattacherjee 2012) Internal validity was achieved by omitting
extraneous variables so that changes in the response to variables is caused by the hypothesized
explanatory variables External validity was achieved by generalizing from Makerere and Gulu
universities to other universities These two universities were chosen because their lecturers have been
motivated earlier their students would have had more exposure to the technology adoption and with that
experience it would be appropriate to capture their perspectives Validity of the student qualitative
instrument was achieved through use of research experts who were used to validate whether the content
in the instrument could get the data required (Ozkan amp Koseler 2009)
Additionally the developed question concepts were derived from past relevant studies This can be
related to Bhardwaj and Goundar (2019) who captured studentsrsquo perceptions on TSL based on the
modification of concepts from relevant past studies Studies on studentsrsquo perceptions taking a
quantitative approach are usually carried out using reliability tests Kim et al (2019) carried out a
reliability test on a questionnaire that was administered to undergraduate students in a university in
Korea using Cronbachrsquos alpha Similarly the researchers used the same alpha to test questions in the
student self-administered questionnaire The outcome variable of the adoption of TSL was
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 190
operationalized as intention to use innovative use and acceptance of TSL with Cronbach alphas of 064
067 070 respectively The organizational factors had a Cronbach alpha of 073 The researchers
followed ethics guidelines to accomplish the study
RESULTS AND ANALYSIS
Background Information
The majority (821) of the students were aged between 21 and 30 years old This is in line with
Bhardwaj and Goundar (2018) who indicated that the majority of the student respondents were between
21 to 30 years old The majority (641) of the student respondents were male while 359 were female
respondents This is in line with Zuvic-Butorac et al (2011) who found that female students
concentrated on art subjects while their male counterparts were in engineering natural science and ICT
Most (410) of the students were in their second year of study followed by first year students (ie
320) The majority of the students (ie 940) had access to email Few (386) students had laptops
This is because these students may not be in position to afford such devices Most (592) of the
respondents revealed that there are functional TSL laboratories in their universities Most of the students
(571) were affiliated to Gulu University For descriptive analysis of means and standard deviations
for selected research variables see Tables 2 and 3 All the data simulations were based on a Likert scale
of 5 Descriptive analysis of the individual (student) presenting modal age gender and level of education
of the whole population of students (ie N =184) is shown in Table 3
Descriptive Statistics
Table 2
Descriptive Statistics for Selected Research Variables (N =184)
Variable Brief Description of Variables M a Min Max SD
Adoption of TSL
Intention to Use
ITU1 Computers 445 1 5 0979
ITU2 CD-ROMs 283 1 5 1468
ITU3 Web-based learning 384 1 5 1344
ITU4 Video conferencing 359 1 5 1449
ITU5 University TSL environments eg Black-Board 366 1 5 1425
Innovative Use
INU1 I am able to expound on what lecturers have provided to me in class using
the Internet
379 1 5 1334
INU2 I am able to make presentations in text audio and visual 380 1 5 1424
INU3 I am able to communicate with other students through online discussions
emails wikis and WhatsApp
371 1 5 1496
Acceptance
ACC1 Computers 452 1 5 0941
ACC2 CD-ROMs 296 1 5 1536
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 191
Variable Brief Description of Variables M a Min Max SD
ACC3 Web-based learning 375 1 5 1388
ACC4 Video conferencing 359 1 5 1376
ACC5 University TSL environments eg Black-Board 361 1 5 1536
Organizational Factors
GUELP1 Goal of university TSL policy 297 1 5 1408
ATIEXICT1 Availability of time to experiment with ICT 322 1 5 1366
AFS1 Availability of financial support 273 1 5 1544
COMAN1 Commitment of management 304 1 5 1362
a A score of 350 indicates that the person has and there was ldquoeg intention to use TSL encouragement
on use of TSL facilities and ldquohindrance to the progress of TSL ISsrdquo on the five-point Likert scale of
1(Very little or no intention to use TSL encouragement on use of TSL facilities and hindrance to the
progress of TSL ISs ) and 5(Very much intention to use TSL greatest encouragement on use of TSL
facilities and very much hindrance to the progress of TSL ISs)
Students had lsquomuchrsquo intention to use TSL facilities For instance they had lsquomuchrsquo intention to use
computers (ITU1) The students had lsquomuchrsquo innovative use of TSL (for instance they were able to make
presentations in text audio and video INU2) They also indicated very much acceptance of TSL For
instance they had very much acceptance of computers (ACC1)
See Table 3 for most frequent characteristics of each individual in the whole student population (ie N
=184)
Table 3
Individual Factors (N = 184)
Individual Factors Rate of Occurrence Most Frequent
Individual Factors
AGE Most frequent age of students 25 Years
GEN Most frequent gender of students Male
LEDUC Most frequent year of study of students Year 2
Cluster Analyses
The researchers used the k-means clustering algorithm with the help of Statistica Software version 133
to generate six clusters The data were standardized Whereas several simulations were carried out (ie1
2 3 4 5 and 6) only the sixth simulation showed acceptable results All 6 simulations yielded p values
less than 005 (see Table 4) Table 4 indicates the measurement of the organizational factors and
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 192
adoption of TSL in universities in Uganda across the six student clusters Table 5 shows the
measurement of the individual factors across the said clusters
Table 4
Cluster Analysis and Analysis of Variance for Students
Cluster
Variable 1
(n = 37)
2
(n = 38)
3
(n = 19)
4
(n = 42)
5
(n = 24)
6
(n = 24)
ANOVA
F p
Adoption of TSL
Intention to Use TSL
ITU1 011 024 002 032 048 -161 244 00
ITU2 -007 -074 033 069 -014 -005 1109 00
ITU3 -101 037 035 058 039 -072 2502 00
ITU4 -084 031 031 059 031 -079 1893 00
ITU5 -056 022 -006 059 029 -078 1159 00
Innovative Use of TSL
INU1 -025 051 -024 065 -013 -122 2075 00
INU2 014 029 -142 049 052 -092 2671 00
INU3 -051 044 -128 061 049 -045 2449 00
Acceptance of TSL
ACC1 023 023 007 039 034 -179 3439 00
ACC2 -021 -085 050 092 018 -052 2579 00
ACC3 -087 041 007 064 033 -081 2219 00
ACC4 -100 027 029 067 057 -086 3169 00
ACC5 -065 001 -013 064 066 -069 1529 00
Organizational Factors
GUELP1 004 032 -024 078 -099 -075 2078 00
ATIEXICT1 019 -051 -069 089 -009 -040 1636 00
AFS1 012 -051 -044 105 -053 -036 2228 00
COMAN1 001 -017 -057 074 -018 -039 835 00
Note Positive values are indicated in bold while negative ones are not in bold
Table 5
Individual Factors per Cluster
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
AGE Most frequent
age of
students
26
Years
25
Years
25
Years
25
Years
26
Years
24
Years
356 00
GEN Most frequent
gender of
students
Male Equal
number
of male
and
female
Female Male Male Male 426 00
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 193
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
LEDUC Most frequent
year of
study of
students
Year 2 Year 2 Year 1 Year 2 Year 4 Year 1 409 00
Qualitative Analysis
Thematic analysis was used in analyzing qualitative data We used Braun and Clarke (2006)rsquos six
thematic analysis steps of familiarization generating initial codes searching reviewing defining and
naming themes and producing a report Studentsrsquo data comprised student interview data items from
which initial extracts were made Familiarization was carried out by reading and re-reading the said data
items Generating initial codes was achieved through capturing features of interest from the student data
set Searching was achieved through grouping student data relevant to potential themes Defining and
naming was achieved by categorizing the themes Finally a report about the student data was produced
The researchers used the most significant interview data that could support the quantitative results
presented in this paper in the discussion of findings section Thus the discussion of findings is
integrative
DISCUSSION OF FINDINGS
In this section qualitative findings have been integrated with the quantitative ones The letter lsquoSrsquo
denotes student Cluster 1 students were ranked third as far as the adoption of TSL is concerned because
of the quite weak alignment between the configurational factors For instance the students had no
intention to use web-based technology This was confirmed by student S5 who revealed that she did not
understand web-based learning These students could not interact with their colleagues using TSL
facilities Students in this cluster never embraced video conferencing technology because it is limited as
reflected in the main themes by the students S1 S3 and S5 However these students had the intention to
use computer technology This is consistent with student S1 who commented that ldquoI have the intention
to use computers for academic purposesrdquo They also had innovative use of TSL shown through their
ability to incorporate text audio and visual technology Furthermore these students accepted computer
technology This is supported by students S1 S2 and S6 who revealed that they use computers because
of the current education trend which demands them to be computer literate for academic purposes and
they are easy to work with
Further analysis of this cluster indicates that the organizational factors encourage these students to use
TSL facilities (see Table 4) Qualitative results from students S1 S4 and S3 respectively had the
following implications on the organizational factors
bull the goal of the TSL learning policy encourages the use of TSL facilities at a minimal level
bull students practise with ICT and also believe that the university indirectly supports them financially by
providing limited wireless fidelity
bull the university management is supportive by designing sessions on how to use computers
A typical student in this cluster was 26 years old male by gender and in his second year of study (see
Table 5) While these students have similar characteristics with those of Cluster 6 they have tried to
adopt TSL facilities compared Cluster 6 students because of their experience with such facilities
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 194
Cluster 2 students ranked second as far as adoption of TSL is concerned For example students in this
cluster revealed lsquomuchrsquo intention to use TSL For instance student S1 confirmed that ldquoWeb-based
learning offers more informationrdquo Students in this cluster were lsquovery muchrsquo capable of expounding on
what lecturers had provided to them in class using the Internet This was through ldquosurfingrdquo the Internet
using the Google search engine as revealed by student S1 Students in this cluster had lsquomuchrsquo
acceptance of TSL facilities such as web-based facilities This is because web-based learning can be
used for research work and expounding on what is taught in class by lecturers as revealed by student S1
This is confirmed by a recent study by Chopra et al (2019) that indicates that students are satisfied by
web-based technology
In relation to the organizational factors students in Cluster 2 agreed that the goal of university TSL
policy encourages their use of TSL facilities The qualitative results suggest that e-discussions can
compel students to use TSL facilities as revealed by Student S3 On average students in this cluster
were aged 25 years the number of male students was equivalent to that of female ones and they were in
their second year of study (see Table 5) These students could be better adopters than those of Cluster 1
because they seemed to have an equal gender distribution Such distribution may account for an unequal
educational technology use among Cluster 1 and 2 students who enjoyed a similar learning experience
(see Tables 4 and 5) Students of this cluster seemed to be better adopters than those of Clusters 1 3 5
and 6 because of their ability to make use of the TSL policy to their advantage (see Tables 4 and 5)
Cluster 3 students were low adopters of TSL because of low alignment between the configurational
factors thus ranked fifth as far as adoption of TSL is concerned These students lacked innovative use of
TSL facilities implying that these students cannot use such facilities to improve their learning
capabilities The same students however registered lsquovery muchrsquo acceptance of CD-ROMs (see Table 4)
This could be because this medium is a dependable way of accessing content by students (Kisanga amp
Ireson 2015)
Students in Cluster 3 perceived that the organizational factors never contributed to their use of TSL
facilities in any way (see Table 4) For example students had no time to experiment with ICT This
could be because students never practise with ICT due to the fact that the course is ldquohecticrdquo and the IT
laboratories are usually closed over the weekend as revealed by student S1 The average age gender
and level of education of a student in this cluster is 25 years female and first-year respectively (see
Table 5) These could be lower adopters of TSL than members of Clusters 2 and 5 because of their
gender Female respondents are disadvantaged when it comes to the use of information technology
(Odewumi 2018) Another plausible reason for the low adoption levels in Cluster 3 compared to those
in Clusters 2 and 1 could be the lack of innovative use of TSL (see Table 4)
Cluster 4 students were the greatest adopters of TSL among the six clusters This is because they had the
lsquogreatestrsquo alignment between the configurational factors These students are eager to use ICT innovative
and embraced TSL They are eager to use CD-ROM technology because such technology is cheap and
stores information as confirmed by students S1 and S6 They can innovatively expound on what
lectures have provided to them in class using the Internet with the help of search engines (such as
Google) as indicated by student S1 They have embraced video conference technology Students S1 S3
and S5 confirmed that they were able to imitate the limited video conferencing learning using the
WhatsApp facility
Students in Cluster 4 perceived that the organizational factors encouraged their use of TSL facilities
High scores were registered on the goal of the university TSL policy time to experiment with ICT
financial support and commitment of university management For instance during the interview process
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 195
student S3 revealed that ldquoa discussion policy for example may improve adoption of [TSL] because
once e-discussions are made they can compel one to use the [TSL] facilitiesrdquo The result from the
interview process on time to experiment with TSL conflicts with the cluster one whereby the majority
of the students never found time to practise with TSL facilities Shah and Cheng (2019) however
indicate that time influences the adoption of TSL facilities Quantitative findings in this cluster on
financial support could be related to those of student S3 who indicated that there was indirect financial
support by their university through the provision of wireless technology On the issue of management
commitment findings are in line with those of student S4 who felt that university management was
committed because they designed computer literacy sessions for them A typical student in this cluster
was 25 years old male by gender and in year 2 of study (see Table 5) This cluster (n = 42) had the
majority of the student respondents among the six clusters
The alignment of the configurational factors in Cluster 5 seemed to be lsquoweakerrsquo than that of Cluster 1
thus this cluster was ranked fourth Whereas the students in this cluster indicated lsquovery muchrsquo adoption
of TSL in some instances the configurational variables registered low scores For instance they had
very much acceptance of TSL environments yet they seemed not to be familiar with the TSL policy
The result on acceptance of TSL environments is parallel to that of Bond et al (2018) who indicated that
such environments are commonly used by students in higher education institutions in Germany The
result on the TSL policy was confirmed by student S4 who revealed that the TSL policy is not
effectively implemented in the university A normal student in this cluster was 26 years old male by
gender and in year 4 of the study (see Table 5) These students could be better adopters of TSL than
those of Clusters 3 and 6 because of their long-time experience with TSL as reflected in their year of
study compared to the said clusters (see Tables 4 and 5) It is not surprising this cluster had the best
distributions of ICTs among students
Similar to Cluster 5 Cluster 6 had 24 respondents (see Table 4) However students in this cluster are
coincidentally ranked as non-adopters of TSL among the six clusters (see Tables 4 and 5) This is
because there is no alignment between the configurational factors resulting in no adoption of TSL
These students were not willing to use IT could not modify their learning capabilities using IT and had
not realised the value of IT tools All 24 respondents in this cluster lsquoconcurredrsquo that the organization
never encouraged their use of TSL facilities This could imply that students were not involved at all
during the adoption of TSL Shah and Cheng (2019) reveal that students perceive that juggling work and
study caring for children financial difficulty and academic writing among other factors affect their
ability to adopt TSL On average students in this cluster were 26 years old male by gender and in year
1 of their study Being in their first year of study could imply that they had little experience with TSL
CONCLUSION
Identification of predictors of successful adoption of TSL among students was achieved using the
Gestalts approach Students perceived that organizational and individual factors predict successful
adoption of TSL Cluster 4 is the most coherent and as such adopted TSL most This is because the
organizational and individual factors were most aligned For example when students in this cluster are
financially supported and are in their second year of study they are eager to use to be innovative with
and embrace TSL And because of their eagerness innovativeness and ability to embrace TSL they have
accumulated more experience than others Cluster 6 students are non-adopters because they are more
inexperienced with TSL than the rest of the students
There seems to be a gap in the use of the non-linear techniques (eg clustering technique) in studies on
studentsrsquo perceptions Most studies for instance Chopra et al (2019) Gerasimova et al (2018) and Shah
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 196
and Cheng (2019) who have measured student perceptions have used linear techniques Thus this study
has closed this gap This study is a benchmark for universities in developing economies to integrate TSL
at university level For instance it should be noted that in order to achieve successful adoption of TSL
among students in universities management must be involved Nabushawo et al (2018) suggest that the
commitment of management can be achieved by collaborating with and training the users of TSL ISs
Since the world is challenged by Corona Virus Disease (COVID) this study can be used as model to
avail learning materials to students without spreading this disease
It should be noted that the rate of adoption of TSL among students is still low yet they have advanced in
age This contradicts Pereira et al (2018) who indicated that adoption of TSL usually takes place at an
early age It is therefore recommended that students should be supported to adopt TSL during their
earlier career years so that universities in Uganda can benefit from this innovation This can be done by
introducing TSL at primary level Universities need to strengthen their management capabilities such as
increasing the time studentsrsquo have to experiment with ICTs Further research is required to develop
strategies that can be adopted to enhance adoption of TSL among students at earlier ages Although this
study was carried out at a particular point in time it can also be carried out longitudinally There are
many indicators of the organization individual (student) and adoption of TSL besides those presented in
the conceptual framework Further research can be carried out on those Besides organization and
individual factors there is need to know the role of other factors in the adoption of TSL among students
While students from only two public universities were considered for this study students from other
universities can be considered as well
ACKNOWLEDGMENTS
The researchers want to thank the Almighty God for the gift of knowledge wisdom and understanding
in the writing of this paper The researchers also thank the Organization for Women in Science for the
Developing World (OWSD) and the Swedish International Development Agency (SIDA) for their
financial support in carrying out the study
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Acosta M L Sisley A Ross J Brailsford I Bhargava A Jacobs R amp Anstice N (2018) Student acceptance of e-
learning methods in the laboratory class in optometry PLOS ONE 13(12) 1-15
httpsdoiorg101371journalpone0209004
Adewole-Odeshi E (2014) Attitude of students towards e-learning in South-West Nigerian universities An application of
technology acceptance model Library Philosophy and Practice Article 1035
Angolia M G amp Pagliari L R (2016) Factors for successful evolution and sustainability of quality distance education
Online Journal of Distance Learning Administration 19(3)
Ayele B A amp Birhanie W K (2018) Acceptance and use of e-learning systems The case of teachers in technology
institutes of Ethiopian universities Applied Informatics 5(1) 1-11 httpsdoiorg101186s40535-018-0048-7
Back D A von Malotky J Sostmann K Peters H Hube R amp Hoff E (2019) Experiences with using e-learning tools
in orthopedics in an uncontrolled field study application Orthopaedics amp Traumatology Surgery amp Research
105(2) 389-393 httpsdoiorg101016jotsr201901002
Bhardwaj A amp Goundar S (2018) Students perspective of elearning and the future of education with MOOCs
International Journal of Computer Engineering 7(5) 248-260
Bhattacherjee A (2012) Social science research Principles methods and practices Textbooks Collection
httpscholarcommonsusfeduoa_textbooks3
Bond M Mariacuten V I Dolch C Bedenlier S amp Zawacki-Ritcher O (2018) Digital transformation in German higher
education Student and teacher perceptions and usage of digital media International Journal of Educational
Technology in Higher Education 15(48) httpsdoiorg101186s41239-018-0130-1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 197
Braun V amp Clarke V (2006) Using thematic analysis in psychology Qualitative Research in Psychology 33 77-101
Chopra G Madan P Jaisingh P amp Bhaskar P (2019) Effectiveness of e-learning portal from studentsrsquo perspective A
structural equation model (SEM) approach Interactive Technology and Smart Education 16(2) 94-116
httpsdoiorg101108ITSE-05-2018-0027
Creswell J W (2014) Research Design Qualitative quantitative and mixed methods approaches (4th ed) Sage
Publications
Damanpour F amp Schneider M (2006) Phases of the adoption of innovation in organisations Effects of environment
organisation and top managers British Journal of Management 17 215ndash236 httpsdoiorg101111j1467-
8551200600498x
Davis F D (1989) Perceived usefulness perceived ease of use and user acceptance of information technology MIS
Quarterly 13(3) 319ndash340 httpsdoiorg102307249008
Drazin R amp Van de Ven A H (1985) Alternative forms of fit in contingency theory Administrative Science Quarterly
30(4) 514-539 httpsdoiorg1023072392695
Drent M amp Meelissen M (2008) Which factors obstruct or stimulate teacher educators to use ICT innovatively
Computers amp Education 51 187ndash199 httpsdoiorg101016jcompedu200705001
Eze S C Chinedu-Eze V C amp Bello A O (2018) The utilisation of e-learning facilities in the educational delivery
system of Nigeria A study of M-University International Journal of Educational Technology in Higher Education
15 (34) 1-20 httpsdoiorg101186s41239-018-0116-z
Ferreira A Teixeira A L amp Dantas A R (2015) Non-technological innovation activities mediate the impacts of the
intra- and extra-organisational contexts on technological innovation outputs Enterprise and Work Innovation
Studies 11 9-43
Gerasimova V G Melamud M R Tutaeva D R Romanova Y D amp Zhenova N A (2018) The adoption of e-learning
technology at the Faculty of Distance Learning of Plekhanov Russian University of Economics Journal of Social
Studies Education Research 9(2) 172-188
Glazier R A Hamann K Pollock P H amp B Wilson B M (2019) Age gender and student success Mixing face-to-face
and online courses in political science Journal of Political Science Education 16(2) 142-157 httpsdoiorg1010801551216920181515636
Greene J C Caracelli V J amp Graham W F (1989) Toward a conceptual framework for mixed method evaluation
designs Educational Evaluation and Policy Analysis 11(3) 255-274 httpsdoiorg1023071163620
Gwamba G Renken J Nampijja J Mayende G amp Muyinda P B (2018) Contextualisation of e-learning systems in
higher education institutions In M Auer amp T Tsiatsos (Eds) Interactive mobile communication technologies and
learning Proceedings of the 11th IMCL conference (pp 44-55) Springer
Hardaker G amp Singh G (2011) The adoption and diffusion of eLearning in UK universities A comparative case study
using Giddenss theory of structuration Campus-Wide Information Systems 28(4) 221ndash233
httpsdoiorg10110810650741111162707
Kim H J Hong A J amp Song H (2019) The roles of academic engagement and digital readiness in studentsrsquo
achievements in university e-learning environments International Journal of Educational Technology in Higher
Education 16(21) 1-18 httpsdoiorg101186s41239-019-0152-3
Kimiloglu H Ozturan M amp Kutlu B (2017) Perceptions about and attitude toward the usage of e-learning in corporate
training Computers in Human Behavior 72 339-349 httpsdoiorg101016jchb201702062
Kisanga D amp Ireson G (2015) Barriers and strategies on adoption of e-learning in Tanzanian higher learning institutions
Lessons for adopters International Journal of Education and Development using Information and Communication
Technology (IJEDICT) 11(2) 126-137
Lee Y-K amp Pituch K (2002 December 10ndash13) Moderators in the adoption of e-learning An investigation of the role of
gender [Article] The Second International Conference on Electronic Business Taipei Taiwan
Lippman P C (2010) Can the physical environment have an impact on the learning environment CELE Exchange
httpsdoiorg1017875km4g21wpwr1-en
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 198
Maina M K amp Nzuki D M (2015) Adoption determinants of e-learning management system in institutions of higher
learning in Kenya A case of selected universities in Nairobi metropolitan International Journal of Business and
Social Science 6(2) 233ndash248
Martin M (1991) The culture of the telephone In PD Hopkins (Ed) Sexmachine Readings in culture gender and
technology (pp 50-74) Indiana University Press
Moakofhi M Leteane O Phiri T Pholele T amp Sebalatlheng P (2017) Challenges of introducing e-learning at
Botswana University of Agriculture and Natural Resources Lecturersrsquo perspective International Journal of
Education and Development using ICT 13( 2) 4-20
Nabushawo H M Muyinda P B Isabwe G M N Prinz A amp Mayende G (2018) Improving online interaction among
blended distance learners at Makerere University In M E Auer D Guralnick amp I Simonics (Eds) Advances in
Intelligent Systems and Computing (pp 63-69) Springer httpsdoiorg101007978-3-319-73210-7_8
Odewumi M O Yusuf M O amp Oputa G O (2018) UTAUT model Intention to use social media for learning interactive
effect of postgraduate gender in South-West Nigeria International Journal of Education and Development using
Information and Communication Technology (IJEDICT) 14(3) 239-251
Okai-Ugbaje S Ardzejewska K amp Imran A (2020) Readiness roles and responsibilities of stakeholders for sustainable
mobile learning adoption in higher education Education Sciences 10(3) 49-69
httpsdoiorg103390educsci10030049
Ozkan S amp Koseler R (2009) Multi-dimensional studentsrsquo evaluation of e-learning systems in the higher education
context An empirical investigation Computers amp Education 53(4) 1285ndash1296
httpsdoiorg101016jcompedu200906011
Parlakkılıccedil A (2014) Change management in transition to e-learning system Qualitative and Quantitative Methods in
Libraries 3(3) 637ndash651
Pereira A Martins P Morgado L amp Fonseca B (2018) Technological proposal using virtual worlds to support
entrepreneurship education for primary school children In M E Auer D Guralnick amp I Simonics (Eds)
Advances in Intelligent Systems and Computing (pp 124-132) Springer
Ramiacuterez-Correa P E Arenas-Gaitaacuten J amp Rondaacuten-Cataluntildea F J (2015) Gender and acceptance of e-learning A multi-
group analysis based on a structural equation model among college students in Chile and Spain PLOS ONE
10(10) 1-17 httpsdoiorg101371journalpone0140460
Rhema A amp Miliszewska I (2014) Analysis of student attitudes towards e-learning The case of engineering students in
Libya Issues in Informing Science and Information Technology 11 169-190 httpsdoiorg10289451987
Rogers E M (2003) Diffusion of innovations (5th ed) Free Press
Salinas J (2004) Cambios metodoloacutegicos con las TIC Estrategias didaacutecticas y entornos virtuales de ensentildeanza-aprendizaje
Bordoacuten 56(3-4) 469-481
Selim H M (2007) Critical success factors for e-learning acceptance Confirmatory factor models Computers amp
Education 49(2) 396ndash413 httpsdoi101016jcompedu200509004
Shah M amp Cheng M (2019) Exploring factors impacting student engagement in open access courses Open learning The
Journal of Open Distance and E-Learning 34(2) 187-202 httpsdoiorg1010800268051320181508337
Singh G ODonoghue J amp Worton H (2005) A study into the effects of elearning on higher education Journal of
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Tchamyou V S (2017) The role of knowledge economy in African business Journal of the Knowledge Economy 8(4)
1189ndash1228 httpsdoiorg101007s13132-016-0417-1
The M M amp Usagawa T (2018) A comparative study of studentsrsquo readiness on e-learning education between Indonesia
and Myanmar American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS) 40(1)
113-124
Venkatraman N (1989) The concept of fit in strategy research Toward verbal and statistical correspondence Academy of
Management Review 9(3) 513-525 httpsdoiorg102307258177
Zuvic-Butorac M Nebic Z amp Nemcanin D (2011) Establishing an institutional framework for an e-learning
implementation Experiences from the University of Rijeka Croatia Journal of Information Technology Education
Innovations in Practice 10 43-56 httpsdoiorg10289451364
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Recommended Citation
-
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Cover Page Footnote
-
- tmp1624440487pdfGS9c9
-
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 187
According to Lippman (2013) studentsrsquo age gender and level of education influence their organizations
This can be observed through variations in the use of TSL policies in place time one takes interacting
with ICTs making use of resources and also participating in activities within an organization Literature
indicates that TSL policies are common within learning institutions (Drent amp Meelissen 2008) Students
can get acquainted with these policies take time to practise with ICT use acquired TSL facilities in the
university and avail themselves to receive information from university management about TSL
Whenever a new technology is adopted it finds a society with inequalities in terms of age gender and
level of education Thus understanding the impact of age gender and level of education in the adoption
of TSL in organizations is paramount Maina and Nzuki (2015) indicate that age is an important factor in
understanding adoption of innovations in learning organizations Pereira et al (2018) indicate that
adoption of technological innovations usually takes place at an early age Adewole-Odeshi (2014)
amplifies that older people tend to have low interaction with the learning organizations resulting in low
adoption of technological innovations in such organizations
The relationship between gender and different environments has been testified (Lee amp Pituch 2002
Martin 1991) Lee and Pituch (2002) suggested that gender should not be left out in information
technology (IT ) adoption models An early study by Martin (1991) on gender differences in technology
adoption and telephone use found that womenrsquos use of the telephone for socialization purposes helped
to expand its use in both residential and business areas Odewumi et al (2018) indicate that females are
disadvantaged when it comes to the adoption of information technology
Damanpour and Schneider (2006) reveal that education level is an individual factor They continue to
argue that education is an important aspect of the adoption of innovations Maina and Nzuki (2015)
agree that level of education impacts on the learning organization during the adoption of innovations In
some instances education is viewed as a management strategy that can ease implementation of specific
innovations in particular organizations (Ferreira et al 2015) There seems to be little research on how
the level of education impacts on the learning organization during the adoption of innovations this study
acted as a basis to fill the gap A first-year student may have no knowledge of the TSL policy in a
particular learning institution which may affect their use of TSL facilities
Theoretical Underpinnings of the Study
The interactions between organizational and individual factors have been presented indicating the
complexities involved These interactions were studied with different theoretical underpinnings Factors
can be studied from a theoretical point of view that seeks to predict TSL from both organizational
(macro) and individual (micro) perspectives (Hardaker amp Singh 2011) Sometimes referred to as the
ldquoduality of structurerdquo factors can be drawn from the works of Giddens lsquotheory of structurationrsquo who
argues that macro and micro perspectives are interlinked Giddens theory is mapped to that of (Rogers
2003)rsquos Diffusion of Innovations Theory to ensure that the factors of adoption of TSL are objectively
measured For instance individual (student) was operationalized according to factors of age gender and
level of education The concept of adoption of TSL has been operationalized as intention to use
innovative use and acceptance of TSL Students can perceive that the factors encourage the adoption of
TSL or not The factors that predict successful adoption of TSL have been studied by using the
conceptual framework in Figure 1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 188
Figure 1
The Conceptual Framework of Predictors of Successful Adoption of Technology- Supported
Learning (TSL) in Universities in Uganda
Gestalts Perspective in this Study
To represent the complex interactions we have incorporated Venkatraman (1989)rsquos Gestalts fit which is
an alignment perspective Venkatraman indicates that alignment aims at balancing related organizational
components This is usually done with the aim of achieving organizational success Gestalts fit has been
achieved by configuring factors that are unique tightly integrated and fairly stable We argue that
measuring organizational and individual factors using a linear model is not appropriate Thus alignment
as Gestalts was adopted to identify those configurations of organizational and individual factors that
predict the adoption of TSL in universities
If configurational factors of the framework (ie organizational and individual factors) are well aligned
then there is greater interaction and thus an increase in the adoption of TSL On the other hand if the
elements are misaligned the level of adoption of TSL is low Thus the following hypotheses were tested
by the researchers The greater the alignment between the organizational and individual factors the more
the i) intention to use ii) innovative use and iii) acceptance of TSL in universities will be
Table 1 provides the definitions of these factors In the conceptual framework the third element is an
outcome of the interaction or interplay between the first and second variables
Table 1
Factors Constructs Employed in the Study
Factors Constructs Operationalization References
Organization Goal of TSL policy availability of time
to experiment with ICT availability of
financial support and commitment of
management
Rogers 2003 Shah amp Cheng
(2019)
Individual (student) Student age gender and level of
education
Glazier et al (2019)
Alignment
Between 1 amp 2
Organization (1) Individual
(2)
Adoption of TSL
in universities in
Uganda (3)
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 189
Factors Constructs Operationalization References
Interaction The interaction between the main factors
ie organization and the individual
affect each other
Drazine amp Van de Ven (1985)
Perception This is the studentrsquos perspective that
indicates whether the factors encourage
adoption or not
Gerasimova et al (2018)
Alignment Level of coherence Venkatraman (1989)
Adoption of TSL Intention to use innovative use and
acceptance of TSL
Rogers (2003) Davis (1989)
METHODOLOGICAL FRAMEWORK
To investigate the predictors of the successful adoption of TSL among students the quantitative survey
mixed and cross-sectional research designs were used (Creswell 2014 Greene et al 1989) A recent
study by Shah and Cheng (2019) carried out on studentsrsquo perceptions used a quantitative research
design Thus the same design was adopted for this study In quantitative designs surveys are usually
used The researchers used a survey to collect data from a total of 184 students The survey was
structured into four main parts background information adoption of TSL organizational and individual
factors Bhardwaj and Goundar (2018) in their study on studentsrsquo perceptions on TSL used a mixed
research approach The researchers adopted the said research approach whereby the largely quantitative
and little qualitative techniques were used
Besides lecturers the population of study included students from both Makerere and Gulu universities
Students were chosen because they are the main users of TSL (Bhardwaj amp Goundar 2018) and they are
faced with challenges in using this type of learning (Gerasimova et al 2018) Purposive and simple
random sampling were used for quantitative data The given universities were purposively chosen
because of the level of knowledge and use of TSL Simple random sampling was used at departmental
level to collect quantitative data from students of agricultural sciences because they are among the main
users of TSL facilities at this level Purposive homogeneous sampling was used for qualitative data A
total of six students were interviewed to complement the questionnaire data
The study took place at a particular point in time hence it was cross-sectional in nature Internal and
external validity checks were used (Bhattacherjee 2012) Internal validity was achieved by omitting
extraneous variables so that changes in the response to variables is caused by the hypothesized
explanatory variables External validity was achieved by generalizing from Makerere and Gulu
universities to other universities These two universities were chosen because their lecturers have been
motivated earlier their students would have had more exposure to the technology adoption and with that
experience it would be appropriate to capture their perspectives Validity of the student qualitative
instrument was achieved through use of research experts who were used to validate whether the content
in the instrument could get the data required (Ozkan amp Koseler 2009)
Additionally the developed question concepts were derived from past relevant studies This can be
related to Bhardwaj and Goundar (2019) who captured studentsrsquo perceptions on TSL based on the
modification of concepts from relevant past studies Studies on studentsrsquo perceptions taking a
quantitative approach are usually carried out using reliability tests Kim et al (2019) carried out a
reliability test on a questionnaire that was administered to undergraduate students in a university in
Korea using Cronbachrsquos alpha Similarly the researchers used the same alpha to test questions in the
student self-administered questionnaire The outcome variable of the adoption of TSL was
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 190
operationalized as intention to use innovative use and acceptance of TSL with Cronbach alphas of 064
067 070 respectively The organizational factors had a Cronbach alpha of 073 The researchers
followed ethics guidelines to accomplish the study
RESULTS AND ANALYSIS
Background Information
The majority (821) of the students were aged between 21 and 30 years old This is in line with
Bhardwaj and Goundar (2018) who indicated that the majority of the student respondents were between
21 to 30 years old The majority (641) of the student respondents were male while 359 were female
respondents This is in line with Zuvic-Butorac et al (2011) who found that female students
concentrated on art subjects while their male counterparts were in engineering natural science and ICT
Most (410) of the students were in their second year of study followed by first year students (ie
320) The majority of the students (ie 940) had access to email Few (386) students had laptops
This is because these students may not be in position to afford such devices Most (592) of the
respondents revealed that there are functional TSL laboratories in their universities Most of the students
(571) were affiliated to Gulu University For descriptive analysis of means and standard deviations
for selected research variables see Tables 2 and 3 All the data simulations were based on a Likert scale
of 5 Descriptive analysis of the individual (student) presenting modal age gender and level of education
of the whole population of students (ie N =184) is shown in Table 3
Descriptive Statistics
Table 2
Descriptive Statistics for Selected Research Variables (N =184)
Variable Brief Description of Variables M a Min Max SD
Adoption of TSL
Intention to Use
ITU1 Computers 445 1 5 0979
ITU2 CD-ROMs 283 1 5 1468
ITU3 Web-based learning 384 1 5 1344
ITU4 Video conferencing 359 1 5 1449
ITU5 University TSL environments eg Black-Board 366 1 5 1425
Innovative Use
INU1 I am able to expound on what lecturers have provided to me in class using
the Internet
379 1 5 1334
INU2 I am able to make presentations in text audio and visual 380 1 5 1424
INU3 I am able to communicate with other students through online discussions
emails wikis and WhatsApp
371 1 5 1496
Acceptance
ACC1 Computers 452 1 5 0941
ACC2 CD-ROMs 296 1 5 1536
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 191
Variable Brief Description of Variables M a Min Max SD
ACC3 Web-based learning 375 1 5 1388
ACC4 Video conferencing 359 1 5 1376
ACC5 University TSL environments eg Black-Board 361 1 5 1536
Organizational Factors
GUELP1 Goal of university TSL policy 297 1 5 1408
ATIEXICT1 Availability of time to experiment with ICT 322 1 5 1366
AFS1 Availability of financial support 273 1 5 1544
COMAN1 Commitment of management 304 1 5 1362
a A score of 350 indicates that the person has and there was ldquoeg intention to use TSL encouragement
on use of TSL facilities and ldquohindrance to the progress of TSL ISsrdquo on the five-point Likert scale of
1(Very little or no intention to use TSL encouragement on use of TSL facilities and hindrance to the
progress of TSL ISs ) and 5(Very much intention to use TSL greatest encouragement on use of TSL
facilities and very much hindrance to the progress of TSL ISs)
Students had lsquomuchrsquo intention to use TSL facilities For instance they had lsquomuchrsquo intention to use
computers (ITU1) The students had lsquomuchrsquo innovative use of TSL (for instance they were able to make
presentations in text audio and video INU2) They also indicated very much acceptance of TSL For
instance they had very much acceptance of computers (ACC1)
See Table 3 for most frequent characteristics of each individual in the whole student population (ie N
=184)
Table 3
Individual Factors (N = 184)
Individual Factors Rate of Occurrence Most Frequent
Individual Factors
AGE Most frequent age of students 25 Years
GEN Most frequent gender of students Male
LEDUC Most frequent year of study of students Year 2
Cluster Analyses
The researchers used the k-means clustering algorithm with the help of Statistica Software version 133
to generate six clusters The data were standardized Whereas several simulations were carried out (ie1
2 3 4 5 and 6) only the sixth simulation showed acceptable results All 6 simulations yielded p values
less than 005 (see Table 4) Table 4 indicates the measurement of the organizational factors and
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 192
adoption of TSL in universities in Uganda across the six student clusters Table 5 shows the
measurement of the individual factors across the said clusters
Table 4
Cluster Analysis and Analysis of Variance for Students
Cluster
Variable 1
(n = 37)
2
(n = 38)
3
(n = 19)
4
(n = 42)
5
(n = 24)
6
(n = 24)
ANOVA
F p
Adoption of TSL
Intention to Use TSL
ITU1 011 024 002 032 048 -161 244 00
ITU2 -007 -074 033 069 -014 -005 1109 00
ITU3 -101 037 035 058 039 -072 2502 00
ITU4 -084 031 031 059 031 -079 1893 00
ITU5 -056 022 -006 059 029 -078 1159 00
Innovative Use of TSL
INU1 -025 051 -024 065 -013 -122 2075 00
INU2 014 029 -142 049 052 -092 2671 00
INU3 -051 044 -128 061 049 -045 2449 00
Acceptance of TSL
ACC1 023 023 007 039 034 -179 3439 00
ACC2 -021 -085 050 092 018 -052 2579 00
ACC3 -087 041 007 064 033 -081 2219 00
ACC4 -100 027 029 067 057 -086 3169 00
ACC5 -065 001 -013 064 066 -069 1529 00
Organizational Factors
GUELP1 004 032 -024 078 -099 -075 2078 00
ATIEXICT1 019 -051 -069 089 -009 -040 1636 00
AFS1 012 -051 -044 105 -053 -036 2228 00
COMAN1 001 -017 -057 074 -018 -039 835 00
Note Positive values are indicated in bold while negative ones are not in bold
Table 5
Individual Factors per Cluster
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
AGE Most frequent
age of
students
26
Years
25
Years
25
Years
25
Years
26
Years
24
Years
356 00
GEN Most frequent
gender of
students
Male Equal
number
of male
and
female
Female Male Male Male 426 00
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 193
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
LEDUC Most frequent
year of
study of
students
Year 2 Year 2 Year 1 Year 2 Year 4 Year 1 409 00
Qualitative Analysis
Thematic analysis was used in analyzing qualitative data We used Braun and Clarke (2006)rsquos six
thematic analysis steps of familiarization generating initial codes searching reviewing defining and
naming themes and producing a report Studentsrsquo data comprised student interview data items from
which initial extracts were made Familiarization was carried out by reading and re-reading the said data
items Generating initial codes was achieved through capturing features of interest from the student data
set Searching was achieved through grouping student data relevant to potential themes Defining and
naming was achieved by categorizing the themes Finally a report about the student data was produced
The researchers used the most significant interview data that could support the quantitative results
presented in this paper in the discussion of findings section Thus the discussion of findings is
integrative
DISCUSSION OF FINDINGS
In this section qualitative findings have been integrated with the quantitative ones The letter lsquoSrsquo
denotes student Cluster 1 students were ranked third as far as the adoption of TSL is concerned because
of the quite weak alignment between the configurational factors For instance the students had no
intention to use web-based technology This was confirmed by student S5 who revealed that she did not
understand web-based learning These students could not interact with their colleagues using TSL
facilities Students in this cluster never embraced video conferencing technology because it is limited as
reflected in the main themes by the students S1 S3 and S5 However these students had the intention to
use computer technology This is consistent with student S1 who commented that ldquoI have the intention
to use computers for academic purposesrdquo They also had innovative use of TSL shown through their
ability to incorporate text audio and visual technology Furthermore these students accepted computer
technology This is supported by students S1 S2 and S6 who revealed that they use computers because
of the current education trend which demands them to be computer literate for academic purposes and
they are easy to work with
Further analysis of this cluster indicates that the organizational factors encourage these students to use
TSL facilities (see Table 4) Qualitative results from students S1 S4 and S3 respectively had the
following implications on the organizational factors
bull the goal of the TSL learning policy encourages the use of TSL facilities at a minimal level
bull students practise with ICT and also believe that the university indirectly supports them financially by
providing limited wireless fidelity
bull the university management is supportive by designing sessions on how to use computers
A typical student in this cluster was 26 years old male by gender and in his second year of study (see
Table 5) While these students have similar characteristics with those of Cluster 6 they have tried to
adopt TSL facilities compared Cluster 6 students because of their experience with such facilities
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 194
Cluster 2 students ranked second as far as adoption of TSL is concerned For example students in this
cluster revealed lsquomuchrsquo intention to use TSL For instance student S1 confirmed that ldquoWeb-based
learning offers more informationrdquo Students in this cluster were lsquovery muchrsquo capable of expounding on
what lecturers had provided to them in class using the Internet This was through ldquosurfingrdquo the Internet
using the Google search engine as revealed by student S1 Students in this cluster had lsquomuchrsquo
acceptance of TSL facilities such as web-based facilities This is because web-based learning can be
used for research work and expounding on what is taught in class by lecturers as revealed by student S1
This is confirmed by a recent study by Chopra et al (2019) that indicates that students are satisfied by
web-based technology
In relation to the organizational factors students in Cluster 2 agreed that the goal of university TSL
policy encourages their use of TSL facilities The qualitative results suggest that e-discussions can
compel students to use TSL facilities as revealed by Student S3 On average students in this cluster
were aged 25 years the number of male students was equivalent to that of female ones and they were in
their second year of study (see Table 5) These students could be better adopters than those of Cluster 1
because they seemed to have an equal gender distribution Such distribution may account for an unequal
educational technology use among Cluster 1 and 2 students who enjoyed a similar learning experience
(see Tables 4 and 5) Students of this cluster seemed to be better adopters than those of Clusters 1 3 5
and 6 because of their ability to make use of the TSL policy to their advantage (see Tables 4 and 5)
Cluster 3 students were low adopters of TSL because of low alignment between the configurational
factors thus ranked fifth as far as adoption of TSL is concerned These students lacked innovative use of
TSL facilities implying that these students cannot use such facilities to improve their learning
capabilities The same students however registered lsquovery muchrsquo acceptance of CD-ROMs (see Table 4)
This could be because this medium is a dependable way of accessing content by students (Kisanga amp
Ireson 2015)
Students in Cluster 3 perceived that the organizational factors never contributed to their use of TSL
facilities in any way (see Table 4) For example students had no time to experiment with ICT This
could be because students never practise with ICT due to the fact that the course is ldquohecticrdquo and the IT
laboratories are usually closed over the weekend as revealed by student S1 The average age gender
and level of education of a student in this cluster is 25 years female and first-year respectively (see
Table 5) These could be lower adopters of TSL than members of Clusters 2 and 5 because of their
gender Female respondents are disadvantaged when it comes to the use of information technology
(Odewumi 2018) Another plausible reason for the low adoption levels in Cluster 3 compared to those
in Clusters 2 and 1 could be the lack of innovative use of TSL (see Table 4)
Cluster 4 students were the greatest adopters of TSL among the six clusters This is because they had the
lsquogreatestrsquo alignment between the configurational factors These students are eager to use ICT innovative
and embraced TSL They are eager to use CD-ROM technology because such technology is cheap and
stores information as confirmed by students S1 and S6 They can innovatively expound on what
lectures have provided to them in class using the Internet with the help of search engines (such as
Google) as indicated by student S1 They have embraced video conference technology Students S1 S3
and S5 confirmed that they were able to imitate the limited video conferencing learning using the
WhatsApp facility
Students in Cluster 4 perceived that the organizational factors encouraged their use of TSL facilities
High scores were registered on the goal of the university TSL policy time to experiment with ICT
financial support and commitment of university management For instance during the interview process
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 195
student S3 revealed that ldquoa discussion policy for example may improve adoption of [TSL] because
once e-discussions are made they can compel one to use the [TSL] facilitiesrdquo The result from the
interview process on time to experiment with TSL conflicts with the cluster one whereby the majority
of the students never found time to practise with TSL facilities Shah and Cheng (2019) however
indicate that time influences the adoption of TSL facilities Quantitative findings in this cluster on
financial support could be related to those of student S3 who indicated that there was indirect financial
support by their university through the provision of wireless technology On the issue of management
commitment findings are in line with those of student S4 who felt that university management was
committed because they designed computer literacy sessions for them A typical student in this cluster
was 25 years old male by gender and in year 2 of study (see Table 5) This cluster (n = 42) had the
majority of the student respondents among the six clusters
The alignment of the configurational factors in Cluster 5 seemed to be lsquoweakerrsquo than that of Cluster 1
thus this cluster was ranked fourth Whereas the students in this cluster indicated lsquovery muchrsquo adoption
of TSL in some instances the configurational variables registered low scores For instance they had
very much acceptance of TSL environments yet they seemed not to be familiar with the TSL policy
The result on acceptance of TSL environments is parallel to that of Bond et al (2018) who indicated that
such environments are commonly used by students in higher education institutions in Germany The
result on the TSL policy was confirmed by student S4 who revealed that the TSL policy is not
effectively implemented in the university A normal student in this cluster was 26 years old male by
gender and in year 4 of the study (see Table 5) These students could be better adopters of TSL than
those of Clusters 3 and 6 because of their long-time experience with TSL as reflected in their year of
study compared to the said clusters (see Tables 4 and 5) It is not surprising this cluster had the best
distributions of ICTs among students
Similar to Cluster 5 Cluster 6 had 24 respondents (see Table 4) However students in this cluster are
coincidentally ranked as non-adopters of TSL among the six clusters (see Tables 4 and 5) This is
because there is no alignment between the configurational factors resulting in no adoption of TSL
These students were not willing to use IT could not modify their learning capabilities using IT and had
not realised the value of IT tools All 24 respondents in this cluster lsquoconcurredrsquo that the organization
never encouraged their use of TSL facilities This could imply that students were not involved at all
during the adoption of TSL Shah and Cheng (2019) reveal that students perceive that juggling work and
study caring for children financial difficulty and academic writing among other factors affect their
ability to adopt TSL On average students in this cluster were 26 years old male by gender and in year
1 of their study Being in their first year of study could imply that they had little experience with TSL
CONCLUSION
Identification of predictors of successful adoption of TSL among students was achieved using the
Gestalts approach Students perceived that organizational and individual factors predict successful
adoption of TSL Cluster 4 is the most coherent and as such adopted TSL most This is because the
organizational and individual factors were most aligned For example when students in this cluster are
financially supported and are in their second year of study they are eager to use to be innovative with
and embrace TSL And because of their eagerness innovativeness and ability to embrace TSL they have
accumulated more experience than others Cluster 6 students are non-adopters because they are more
inexperienced with TSL than the rest of the students
There seems to be a gap in the use of the non-linear techniques (eg clustering technique) in studies on
studentsrsquo perceptions Most studies for instance Chopra et al (2019) Gerasimova et al (2018) and Shah
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 196
and Cheng (2019) who have measured student perceptions have used linear techniques Thus this study
has closed this gap This study is a benchmark for universities in developing economies to integrate TSL
at university level For instance it should be noted that in order to achieve successful adoption of TSL
among students in universities management must be involved Nabushawo et al (2018) suggest that the
commitment of management can be achieved by collaborating with and training the users of TSL ISs
Since the world is challenged by Corona Virus Disease (COVID) this study can be used as model to
avail learning materials to students without spreading this disease
It should be noted that the rate of adoption of TSL among students is still low yet they have advanced in
age This contradicts Pereira et al (2018) who indicated that adoption of TSL usually takes place at an
early age It is therefore recommended that students should be supported to adopt TSL during their
earlier career years so that universities in Uganda can benefit from this innovation This can be done by
introducing TSL at primary level Universities need to strengthen their management capabilities such as
increasing the time studentsrsquo have to experiment with ICTs Further research is required to develop
strategies that can be adopted to enhance adoption of TSL among students at earlier ages Although this
study was carried out at a particular point in time it can also be carried out longitudinally There are
many indicators of the organization individual (student) and adoption of TSL besides those presented in
the conceptual framework Further research can be carried out on those Besides organization and
individual factors there is need to know the role of other factors in the adoption of TSL among students
While students from only two public universities were considered for this study students from other
universities can be considered as well
ACKNOWLEDGMENTS
The researchers want to thank the Almighty God for the gift of knowledge wisdom and understanding
in the writing of this paper The researchers also thank the Organization for Women in Science for the
Developing World (OWSD) and the Swedish International Development Agency (SIDA) for their
financial support in carrying out the study
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httpsdoiorg101371journalpone0209004
Adewole-Odeshi E (2014) Attitude of students towards e-learning in South-West Nigerian universities An application of
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Angolia M G amp Pagliari L R (2016) Factors for successful evolution and sustainability of quality distance education
Online Journal of Distance Learning Administration 19(3)
Ayele B A amp Birhanie W K (2018) Acceptance and use of e-learning systems The case of teachers in technology
institutes of Ethiopian universities Applied Informatics 5(1) 1-11 httpsdoiorg101186s40535-018-0048-7
Back D A von Malotky J Sostmann K Peters H Hube R amp Hoff E (2019) Experiences with using e-learning tools
in orthopedics in an uncontrolled field study application Orthopaedics amp Traumatology Surgery amp Research
105(2) 389-393 httpsdoiorg101016jotsr201901002
Bhardwaj A amp Goundar S (2018) Students perspective of elearning and the future of education with MOOCs
International Journal of Computer Engineering 7(5) 248-260
Bhattacherjee A (2012) Social science research Principles methods and practices Textbooks Collection
httpscholarcommonsusfeduoa_textbooks3
Bond M Mariacuten V I Dolch C Bedenlier S amp Zawacki-Ritcher O (2018) Digital transformation in German higher
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Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 197
Braun V amp Clarke V (2006) Using thematic analysis in psychology Qualitative Research in Psychology 33 77-101
Chopra G Madan P Jaisingh P amp Bhaskar P (2019) Effectiveness of e-learning portal from studentsrsquo perspective A
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httpsdoiorg101108ITSE-05-2018-0027
Creswell J W (2014) Research Design Qualitative quantitative and mixed methods approaches (4th ed) Sage
Publications
Damanpour F amp Schneider M (2006) Phases of the adoption of innovation in organisations Effects of environment
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8551200600498x
Davis F D (1989) Perceived usefulness perceived ease of use and user acceptance of information technology MIS
Quarterly 13(3) 319ndash340 httpsdoiorg102307249008
Drazin R amp Van de Ven A H (1985) Alternative forms of fit in contingency theory Administrative Science Quarterly
30(4) 514-539 httpsdoiorg1023072392695
Drent M amp Meelissen M (2008) Which factors obstruct or stimulate teacher educators to use ICT innovatively
Computers amp Education 51 187ndash199 httpsdoiorg101016jcompedu200705001
Eze S C Chinedu-Eze V C amp Bello A O (2018) The utilisation of e-learning facilities in the educational delivery
system of Nigeria A study of M-University International Journal of Educational Technology in Higher Education
15 (34) 1-20 httpsdoiorg101186s41239-018-0116-z
Ferreira A Teixeira A L amp Dantas A R (2015) Non-technological innovation activities mediate the impacts of the
intra- and extra-organisational contexts on technological innovation outputs Enterprise and Work Innovation
Studies 11 9-43
Gerasimova V G Melamud M R Tutaeva D R Romanova Y D amp Zhenova N A (2018) The adoption of e-learning
technology at the Faculty of Distance Learning of Plekhanov Russian University of Economics Journal of Social
Studies Education Research 9(2) 172-188
Glazier R A Hamann K Pollock P H amp B Wilson B M (2019) Age gender and student success Mixing face-to-face
and online courses in political science Journal of Political Science Education 16(2) 142-157 httpsdoiorg1010801551216920181515636
Greene J C Caracelli V J amp Graham W F (1989) Toward a conceptual framework for mixed method evaluation
designs Educational Evaluation and Policy Analysis 11(3) 255-274 httpsdoiorg1023071163620
Gwamba G Renken J Nampijja J Mayende G amp Muyinda P B (2018) Contextualisation of e-learning systems in
higher education institutions In M Auer amp T Tsiatsos (Eds) Interactive mobile communication technologies and
learning Proceedings of the 11th IMCL conference (pp 44-55) Springer
Hardaker G amp Singh G (2011) The adoption and diffusion of eLearning in UK universities A comparative case study
using Giddenss theory of structuration Campus-Wide Information Systems 28(4) 221ndash233
httpsdoiorg10110810650741111162707
Kim H J Hong A J amp Song H (2019) The roles of academic engagement and digital readiness in studentsrsquo
achievements in university e-learning environments International Journal of Educational Technology in Higher
Education 16(21) 1-18 httpsdoiorg101186s41239-019-0152-3
Kimiloglu H Ozturan M amp Kutlu B (2017) Perceptions about and attitude toward the usage of e-learning in corporate
training Computers in Human Behavior 72 339-349 httpsdoiorg101016jchb201702062
Kisanga D amp Ireson G (2015) Barriers and strategies on adoption of e-learning in Tanzanian higher learning institutions
Lessons for adopters International Journal of Education and Development using Information and Communication
Technology (IJEDICT) 11(2) 126-137
Lee Y-K amp Pituch K (2002 December 10ndash13) Moderators in the adoption of e-learning An investigation of the role of
gender [Article] The Second International Conference on Electronic Business Taipei Taiwan
Lippman P C (2010) Can the physical environment have an impact on the learning environment CELE Exchange
httpsdoiorg1017875km4g21wpwr1-en
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The African Journal of Information Systems Volume 13 Issue 2 Article 3 198
Maina M K amp Nzuki D M (2015) Adoption determinants of e-learning management system in institutions of higher
learning in Kenya A case of selected universities in Nairobi metropolitan International Journal of Business and
Social Science 6(2) 233ndash248
Martin M (1991) The culture of the telephone In PD Hopkins (Ed) Sexmachine Readings in culture gender and
technology (pp 50-74) Indiana University Press
Moakofhi M Leteane O Phiri T Pholele T amp Sebalatlheng P (2017) Challenges of introducing e-learning at
Botswana University of Agriculture and Natural Resources Lecturersrsquo perspective International Journal of
Education and Development using ICT 13( 2) 4-20
Nabushawo H M Muyinda P B Isabwe G M N Prinz A amp Mayende G (2018) Improving online interaction among
blended distance learners at Makerere University In M E Auer D Guralnick amp I Simonics (Eds) Advances in
Intelligent Systems and Computing (pp 63-69) Springer httpsdoiorg101007978-3-319-73210-7_8
Odewumi M O Yusuf M O amp Oputa G O (2018) UTAUT model Intention to use social media for learning interactive
effect of postgraduate gender in South-West Nigeria International Journal of Education and Development using
Information and Communication Technology (IJEDICT) 14(3) 239-251
Okai-Ugbaje S Ardzejewska K amp Imran A (2020) Readiness roles and responsibilities of stakeholders for sustainable
mobile learning adoption in higher education Education Sciences 10(3) 49-69
httpsdoiorg103390educsci10030049
Ozkan S amp Koseler R (2009) Multi-dimensional studentsrsquo evaluation of e-learning systems in the higher education
context An empirical investigation Computers amp Education 53(4) 1285ndash1296
httpsdoiorg101016jcompedu200906011
Parlakkılıccedil A (2014) Change management in transition to e-learning system Qualitative and Quantitative Methods in
Libraries 3(3) 637ndash651
Pereira A Martins P Morgado L amp Fonseca B (2018) Technological proposal using virtual worlds to support
entrepreneurship education for primary school children In M E Auer D Guralnick amp I Simonics (Eds)
Advances in Intelligent Systems and Computing (pp 124-132) Springer
Ramiacuterez-Correa P E Arenas-Gaitaacuten J amp Rondaacuten-Cataluntildea F J (2015) Gender and acceptance of e-learning A multi-
group analysis based on a structural equation model among college students in Chile and Spain PLOS ONE
10(10) 1-17 httpsdoiorg101371journalpone0140460
Rhema A amp Miliszewska I (2014) Analysis of student attitudes towards e-learning The case of engineering students in
Libya Issues in Informing Science and Information Technology 11 169-190 httpsdoiorg10289451987
Rogers E M (2003) Diffusion of innovations (5th ed) Free Press
Salinas J (2004) Cambios metodoloacutegicos con las TIC Estrategias didaacutecticas y entornos virtuales de ensentildeanza-aprendizaje
Bordoacuten 56(3-4) 469-481
Selim H M (2007) Critical success factors for e-learning acceptance Confirmatory factor models Computers amp
Education 49(2) 396ndash413 httpsdoi101016jcompedu200509004
Shah M amp Cheng M (2019) Exploring factors impacting student engagement in open access courses Open learning The
Journal of Open Distance and E-Learning 34(2) 187-202 httpsdoiorg1010800268051320181508337
Singh G ODonoghue J amp Worton H (2005) A study into the effects of elearning on higher education Journal of
University Teaching and Learning Practice 2(1) 13-24
Tchamyou V S (2017) The role of knowledge economy in African business Journal of the Knowledge Economy 8(4)
1189ndash1228 httpsdoiorg101007s13132-016-0417-1
The M M amp Usagawa T (2018) A comparative study of studentsrsquo readiness on e-learning education between Indonesia
and Myanmar American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS) 40(1)
113-124
Venkatraman N (1989) The concept of fit in strategy research Toward verbal and statistical correspondence Academy of
Management Review 9(3) 513-525 httpsdoiorg102307258177
Zuvic-Butorac M Nebic Z amp Nemcanin D (2011) Establishing an institutional framework for an e-learning
implementation Experiences from the University of Rijeka Croatia Journal of Information Technology Education
Innovations in Practice 10 43-56 httpsdoiorg10289451364
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Recommended Citation
-
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Cover Page Footnote
-
- tmp1624440487pdfGS9c9
-
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 188
Figure 1
The Conceptual Framework of Predictors of Successful Adoption of Technology- Supported
Learning (TSL) in Universities in Uganda
Gestalts Perspective in this Study
To represent the complex interactions we have incorporated Venkatraman (1989)rsquos Gestalts fit which is
an alignment perspective Venkatraman indicates that alignment aims at balancing related organizational
components This is usually done with the aim of achieving organizational success Gestalts fit has been
achieved by configuring factors that are unique tightly integrated and fairly stable We argue that
measuring organizational and individual factors using a linear model is not appropriate Thus alignment
as Gestalts was adopted to identify those configurations of organizational and individual factors that
predict the adoption of TSL in universities
If configurational factors of the framework (ie organizational and individual factors) are well aligned
then there is greater interaction and thus an increase in the adoption of TSL On the other hand if the
elements are misaligned the level of adoption of TSL is low Thus the following hypotheses were tested
by the researchers The greater the alignment between the organizational and individual factors the more
the i) intention to use ii) innovative use and iii) acceptance of TSL in universities will be
Table 1 provides the definitions of these factors In the conceptual framework the third element is an
outcome of the interaction or interplay between the first and second variables
Table 1
Factors Constructs Employed in the Study
Factors Constructs Operationalization References
Organization Goal of TSL policy availability of time
to experiment with ICT availability of
financial support and commitment of
management
Rogers 2003 Shah amp Cheng
(2019)
Individual (student) Student age gender and level of
education
Glazier et al (2019)
Alignment
Between 1 amp 2
Organization (1) Individual
(2)
Adoption of TSL
in universities in
Uganda (3)
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 189
Factors Constructs Operationalization References
Interaction The interaction between the main factors
ie organization and the individual
affect each other
Drazine amp Van de Ven (1985)
Perception This is the studentrsquos perspective that
indicates whether the factors encourage
adoption or not
Gerasimova et al (2018)
Alignment Level of coherence Venkatraman (1989)
Adoption of TSL Intention to use innovative use and
acceptance of TSL
Rogers (2003) Davis (1989)
METHODOLOGICAL FRAMEWORK
To investigate the predictors of the successful adoption of TSL among students the quantitative survey
mixed and cross-sectional research designs were used (Creswell 2014 Greene et al 1989) A recent
study by Shah and Cheng (2019) carried out on studentsrsquo perceptions used a quantitative research
design Thus the same design was adopted for this study In quantitative designs surveys are usually
used The researchers used a survey to collect data from a total of 184 students The survey was
structured into four main parts background information adoption of TSL organizational and individual
factors Bhardwaj and Goundar (2018) in their study on studentsrsquo perceptions on TSL used a mixed
research approach The researchers adopted the said research approach whereby the largely quantitative
and little qualitative techniques were used
Besides lecturers the population of study included students from both Makerere and Gulu universities
Students were chosen because they are the main users of TSL (Bhardwaj amp Goundar 2018) and they are
faced with challenges in using this type of learning (Gerasimova et al 2018) Purposive and simple
random sampling were used for quantitative data The given universities were purposively chosen
because of the level of knowledge and use of TSL Simple random sampling was used at departmental
level to collect quantitative data from students of agricultural sciences because they are among the main
users of TSL facilities at this level Purposive homogeneous sampling was used for qualitative data A
total of six students were interviewed to complement the questionnaire data
The study took place at a particular point in time hence it was cross-sectional in nature Internal and
external validity checks were used (Bhattacherjee 2012) Internal validity was achieved by omitting
extraneous variables so that changes in the response to variables is caused by the hypothesized
explanatory variables External validity was achieved by generalizing from Makerere and Gulu
universities to other universities These two universities were chosen because their lecturers have been
motivated earlier their students would have had more exposure to the technology adoption and with that
experience it would be appropriate to capture their perspectives Validity of the student qualitative
instrument was achieved through use of research experts who were used to validate whether the content
in the instrument could get the data required (Ozkan amp Koseler 2009)
Additionally the developed question concepts were derived from past relevant studies This can be
related to Bhardwaj and Goundar (2019) who captured studentsrsquo perceptions on TSL based on the
modification of concepts from relevant past studies Studies on studentsrsquo perceptions taking a
quantitative approach are usually carried out using reliability tests Kim et al (2019) carried out a
reliability test on a questionnaire that was administered to undergraduate students in a university in
Korea using Cronbachrsquos alpha Similarly the researchers used the same alpha to test questions in the
student self-administered questionnaire The outcome variable of the adoption of TSL was
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 190
operationalized as intention to use innovative use and acceptance of TSL with Cronbach alphas of 064
067 070 respectively The organizational factors had a Cronbach alpha of 073 The researchers
followed ethics guidelines to accomplish the study
RESULTS AND ANALYSIS
Background Information
The majority (821) of the students were aged between 21 and 30 years old This is in line with
Bhardwaj and Goundar (2018) who indicated that the majority of the student respondents were between
21 to 30 years old The majority (641) of the student respondents were male while 359 were female
respondents This is in line with Zuvic-Butorac et al (2011) who found that female students
concentrated on art subjects while their male counterparts were in engineering natural science and ICT
Most (410) of the students were in their second year of study followed by first year students (ie
320) The majority of the students (ie 940) had access to email Few (386) students had laptops
This is because these students may not be in position to afford such devices Most (592) of the
respondents revealed that there are functional TSL laboratories in their universities Most of the students
(571) were affiliated to Gulu University For descriptive analysis of means and standard deviations
for selected research variables see Tables 2 and 3 All the data simulations were based on a Likert scale
of 5 Descriptive analysis of the individual (student) presenting modal age gender and level of education
of the whole population of students (ie N =184) is shown in Table 3
Descriptive Statistics
Table 2
Descriptive Statistics for Selected Research Variables (N =184)
Variable Brief Description of Variables M a Min Max SD
Adoption of TSL
Intention to Use
ITU1 Computers 445 1 5 0979
ITU2 CD-ROMs 283 1 5 1468
ITU3 Web-based learning 384 1 5 1344
ITU4 Video conferencing 359 1 5 1449
ITU5 University TSL environments eg Black-Board 366 1 5 1425
Innovative Use
INU1 I am able to expound on what lecturers have provided to me in class using
the Internet
379 1 5 1334
INU2 I am able to make presentations in text audio and visual 380 1 5 1424
INU3 I am able to communicate with other students through online discussions
emails wikis and WhatsApp
371 1 5 1496
Acceptance
ACC1 Computers 452 1 5 0941
ACC2 CD-ROMs 296 1 5 1536
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 191
Variable Brief Description of Variables M a Min Max SD
ACC3 Web-based learning 375 1 5 1388
ACC4 Video conferencing 359 1 5 1376
ACC5 University TSL environments eg Black-Board 361 1 5 1536
Organizational Factors
GUELP1 Goal of university TSL policy 297 1 5 1408
ATIEXICT1 Availability of time to experiment with ICT 322 1 5 1366
AFS1 Availability of financial support 273 1 5 1544
COMAN1 Commitment of management 304 1 5 1362
a A score of 350 indicates that the person has and there was ldquoeg intention to use TSL encouragement
on use of TSL facilities and ldquohindrance to the progress of TSL ISsrdquo on the five-point Likert scale of
1(Very little or no intention to use TSL encouragement on use of TSL facilities and hindrance to the
progress of TSL ISs ) and 5(Very much intention to use TSL greatest encouragement on use of TSL
facilities and very much hindrance to the progress of TSL ISs)
Students had lsquomuchrsquo intention to use TSL facilities For instance they had lsquomuchrsquo intention to use
computers (ITU1) The students had lsquomuchrsquo innovative use of TSL (for instance they were able to make
presentations in text audio and video INU2) They also indicated very much acceptance of TSL For
instance they had very much acceptance of computers (ACC1)
See Table 3 for most frequent characteristics of each individual in the whole student population (ie N
=184)
Table 3
Individual Factors (N = 184)
Individual Factors Rate of Occurrence Most Frequent
Individual Factors
AGE Most frequent age of students 25 Years
GEN Most frequent gender of students Male
LEDUC Most frequent year of study of students Year 2
Cluster Analyses
The researchers used the k-means clustering algorithm with the help of Statistica Software version 133
to generate six clusters The data were standardized Whereas several simulations were carried out (ie1
2 3 4 5 and 6) only the sixth simulation showed acceptable results All 6 simulations yielded p values
less than 005 (see Table 4) Table 4 indicates the measurement of the organizational factors and
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 192
adoption of TSL in universities in Uganda across the six student clusters Table 5 shows the
measurement of the individual factors across the said clusters
Table 4
Cluster Analysis and Analysis of Variance for Students
Cluster
Variable 1
(n = 37)
2
(n = 38)
3
(n = 19)
4
(n = 42)
5
(n = 24)
6
(n = 24)
ANOVA
F p
Adoption of TSL
Intention to Use TSL
ITU1 011 024 002 032 048 -161 244 00
ITU2 -007 -074 033 069 -014 -005 1109 00
ITU3 -101 037 035 058 039 -072 2502 00
ITU4 -084 031 031 059 031 -079 1893 00
ITU5 -056 022 -006 059 029 -078 1159 00
Innovative Use of TSL
INU1 -025 051 -024 065 -013 -122 2075 00
INU2 014 029 -142 049 052 -092 2671 00
INU3 -051 044 -128 061 049 -045 2449 00
Acceptance of TSL
ACC1 023 023 007 039 034 -179 3439 00
ACC2 -021 -085 050 092 018 -052 2579 00
ACC3 -087 041 007 064 033 -081 2219 00
ACC4 -100 027 029 067 057 -086 3169 00
ACC5 -065 001 -013 064 066 -069 1529 00
Organizational Factors
GUELP1 004 032 -024 078 -099 -075 2078 00
ATIEXICT1 019 -051 -069 089 -009 -040 1636 00
AFS1 012 -051 -044 105 -053 -036 2228 00
COMAN1 001 -017 -057 074 -018 -039 835 00
Note Positive values are indicated in bold while negative ones are not in bold
Table 5
Individual Factors per Cluster
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
AGE Most frequent
age of
students
26
Years
25
Years
25
Years
25
Years
26
Years
24
Years
356 00
GEN Most frequent
gender of
students
Male Equal
number
of male
and
female
Female Male Male Male 426 00
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 193
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
LEDUC Most frequent
year of
study of
students
Year 2 Year 2 Year 1 Year 2 Year 4 Year 1 409 00
Qualitative Analysis
Thematic analysis was used in analyzing qualitative data We used Braun and Clarke (2006)rsquos six
thematic analysis steps of familiarization generating initial codes searching reviewing defining and
naming themes and producing a report Studentsrsquo data comprised student interview data items from
which initial extracts were made Familiarization was carried out by reading and re-reading the said data
items Generating initial codes was achieved through capturing features of interest from the student data
set Searching was achieved through grouping student data relevant to potential themes Defining and
naming was achieved by categorizing the themes Finally a report about the student data was produced
The researchers used the most significant interview data that could support the quantitative results
presented in this paper in the discussion of findings section Thus the discussion of findings is
integrative
DISCUSSION OF FINDINGS
In this section qualitative findings have been integrated with the quantitative ones The letter lsquoSrsquo
denotes student Cluster 1 students were ranked third as far as the adoption of TSL is concerned because
of the quite weak alignment between the configurational factors For instance the students had no
intention to use web-based technology This was confirmed by student S5 who revealed that she did not
understand web-based learning These students could not interact with their colleagues using TSL
facilities Students in this cluster never embraced video conferencing technology because it is limited as
reflected in the main themes by the students S1 S3 and S5 However these students had the intention to
use computer technology This is consistent with student S1 who commented that ldquoI have the intention
to use computers for academic purposesrdquo They also had innovative use of TSL shown through their
ability to incorporate text audio and visual technology Furthermore these students accepted computer
technology This is supported by students S1 S2 and S6 who revealed that they use computers because
of the current education trend which demands them to be computer literate for academic purposes and
they are easy to work with
Further analysis of this cluster indicates that the organizational factors encourage these students to use
TSL facilities (see Table 4) Qualitative results from students S1 S4 and S3 respectively had the
following implications on the organizational factors
bull the goal of the TSL learning policy encourages the use of TSL facilities at a minimal level
bull students practise with ICT and also believe that the university indirectly supports them financially by
providing limited wireless fidelity
bull the university management is supportive by designing sessions on how to use computers
A typical student in this cluster was 26 years old male by gender and in his second year of study (see
Table 5) While these students have similar characteristics with those of Cluster 6 they have tried to
adopt TSL facilities compared Cluster 6 students because of their experience with such facilities
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 194
Cluster 2 students ranked second as far as adoption of TSL is concerned For example students in this
cluster revealed lsquomuchrsquo intention to use TSL For instance student S1 confirmed that ldquoWeb-based
learning offers more informationrdquo Students in this cluster were lsquovery muchrsquo capable of expounding on
what lecturers had provided to them in class using the Internet This was through ldquosurfingrdquo the Internet
using the Google search engine as revealed by student S1 Students in this cluster had lsquomuchrsquo
acceptance of TSL facilities such as web-based facilities This is because web-based learning can be
used for research work and expounding on what is taught in class by lecturers as revealed by student S1
This is confirmed by a recent study by Chopra et al (2019) that indicates that students are satisfied by
web-based technology
In relation to the organizational factors students in Cluster 2 agreed that the goal of university TSL
policy encourages their use of TSL facilities The qualitative results suggest that e-discussions can
compel students to use TSL facilities as revealed by Student S3 On average students in this cluster
were aged 25 years the number of male students was equivalent to that of female ones and they were in
their second year of study (see Table 5) These students could be better adopters than those of Cluster 1
because they seemed to have an equal gender distribution Such distribution may account for an unequal
educational technology use among Cluster 1 and 2 students who enjoyed a similar learning experience
(see Tables 4 and 5) Students of this cluster seemed to be better adopters than those of Clusters 1 3 5
and 6 because of their ability to make use of the TSL policy to their advantage (see Tables 4 and 5)
Cluster 3 students were low adopters of TSL because of low alignment between the configurational
factors thus ranked fifth as far as adoption of TSL is concerned These students lacked innovative use of
TSL facilities implying that these students cannot use such facilities to improve their learning
capabilities The same students however registered lsquovery muchrsquo acceptance of CD-ROMs (see Table 4)
This could be because this medium is a dependable way of accessing content by students (Kisanga amp
Ireson 2015)
Students in Cluster 3 perceived that the organizational factors never contributed to their use of TSL
facilities in any way (see Table 4) For example students had no time to experiment with ICT This
could be because students never practise with ICT due to the fact that the course is ldquohecticrdquo and the IT
laboratories are usually closed over the weekend as revealed by student S1 The average age gender
and level of education of a student in this cluster is 25 years female and first-year respectively (see
Table 5) These could be lower adopters of TSL than members of Clusters 2 and 5 because of their
gender Female respondents are disadvantaged when it comes to the use of information technology
(Odewumi 2018) Another plausible reason for the low adoption levels in Cluster 3 compared to those
in Clusters 2 and 1 could be the lack of innovative use of TSL (see Table 4)
Cluster 4 students were the greatest adopters of TSL among the six clusters This is because they had the
lsquogreatestrsquo alignment between the configurational factors These students are eager to use ICT innovative
and embraced TSL They are eager to use CD-ROM technology because such technology is cheap and
stores information as confirmed by students S1 and S6 They can innovatively expound on what
lectures have provided to them in class using the Internet with the help of search engines (such as
Google) as indicated by student S1 They have embraced video conference technology Students S1 S3
and S5 confirmed that they were able to imitate the limited video conferencing learning using the
WhatsApp facility
Students in Cluster 4 perceived that the organizational factors encouraged their use of TSL facilities
High scores were registered on the goal of the university TSL policy time to experiment with ICT
financial support and commitment of university management For instance during the interview process
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 195
student S3 revealed that ldquoa discussion policy for example may improve adoption of [TSL] because
once e-discussions are made they can compel one to use the [TSL] facilitiesrdquo The result from the
interview process on time to experiment with TSL conflicts with the cluster one whereby the majority
of the students never found time to practise with TSL facilities Shah and Cheng (2019) however
indicate that time influences the adoption of TSL facilities Quantitative findings in this cluster on
financial support could be related to those of student S3 who indicated that there was indirect financial
support by their university through the provision of wireless technology On the issue of management
commitment findings are in line with those of student S4 who felt that university management was
committed because they designed computer literacy sessions for them A typical student in this cluster
was 25 years old male by gender and in year 2 of study (see Table 5) This cluster (n = 42) had the
majority of the student respondents among the six clusters
The alignment of the configurational factors in Cluster 5 seemed to be lsquoweakerrsquo than that of Cluster 1
thus this cluster was ranked fourth Whereas the students in this cluster indicated lsquovery muchrsquo adoption
of TSL in some instances the configurational variables registered low scores For instance they had
very much acceptance of TSL environments yet they seemed not to be familiar with the TSL policy
The result on acceptance of TSL environments is parallel to that of Bond et al (2018) who indicated that
such environments are commonly used by students in higher education institutions in Germany The
result on the TSL policy was confirmed by student S4 who revealed that the TSL policy is not
effectively implemented in the university A normal student in this cluster was 26 years old male by
gender and in year 4 of the study (see Table 5) These students could be better adopters of TSL than
those of Clusters 3 and 6 because of their long-time experience with TSL as reflected in their year of
study compared to the said clusters (see Tables 4 and 5) It is not surprising this cluster had the best
distributions of ICTs among students
Similar to Cluster 5 Cluster 6 had 24 respondents (see Table 4) However students in this cluster are
coincidentally ranked as non-adopters of TSL among the six clusters (see Tables 4 and 5) This is
because there is no alignment between the configurational factors resulting in no adoption of TSL
These students were not willing to use IT could not modify their learning capabilities using IT and had
not realised the value of IT tools All 24 respondents in this cluster lsquoconcurredrsquo that the organization
never encouraged their use of TSL facilities This could imply that students were not involved at all
during the adoption of TSL Shah and Cheng (2019) reveal that students perceive that juggling work and
study caring for children financial difficulty and academic writing among other factors affect their
ability to adopt TSL On average students in this cluster were 26 years old male by gender and in year
1 of their study Being in their first year of study could imply that they had little experience with TSL
CONCLUSION
Identification of predictors of successful adoption of TSL among students was achieved using the
Gestalts approach Students perceived that organizational and individual factors predict successful
adoption of TSL Cluster 4 is the most coherent and as such adopted TSL most This is because the
organizational and individual factors were most aligned For example when students in this cluster are
financially supported and are in their second year of study they are eager to use to be innovative with
and embrace TSL And because of their eagerness innovativeness and ability to embrace TSL they have
accumulated more experience than others Cluster 6 students are non-adopters because they are more
inexperienced with TSL than the rest of the students
There seems to be a gap in the use of the non-linear techniques (eg clustering technique) in studies on
studentsrsquo perceptions Most studies for instance Chopra et al (2019) Gerasimova et al (2018) and Shah
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 196
and Cheng (2019) who have measured student perceptions have used linear techniques Thus this study
has closed this gap This study is a benchmark for universities in developing economies to integrate TSL
at university level For instance it should be noted that in order to achieve successful adoption of TSL
among students in universities management must be involved Nabushawo et al (2018) suggest that the
commitment of management can be achieved by collaborating with and training the users of TSL ISs
Since the world is challenged by Corona Virus Disease (COVID) this study can be used as model to
avail learning materials to students without spreading this disease
It should be noted that the rate of adoption of TSL among students is still low yet they have advanced in
age This contradicts Pereira et al (2018) who indicated that adoption of TSL usually takes place at an
early age It is therefore recommended that students should be supported to adopt TSL during their
earlier career years so that universities in Uganda can benefit from this innovation This can be done by
introducing TSL at primary level Universities need to strengthen their management capabilities such as
increasing the time studentsrsquo have to experiment with ICTs Further research is required to develop
strategies that can be adopted to enhance adoption of TSL among students at earlier ages Although this
study was carried out at a particular point in time it can also be carried out longitudinally There are
many indicators of the organization individual (student) and adoption of TSL besides those presented in
the conceptual framework Further research can be carried out on those Besides organization and
individual factors there is need to know the role of other factors in the adoption of TSL among students
While students from only two public universities were considered for this study students from other
universities can be considered as well
ACKNOWLEDGMENTS
The researchers want to thank the Almighty God for the gift of knowledge wisdom and understanding
in the writing of this paper The researchers also thank the Organization for Women in Science for the
Developing World (OWSD) and the Swedish International Development Agency (SIDA) for their
financial support in carrying out the study
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Acosta M L Sisley A Ross J Brailsford I Bhargava A Jacobs R amp Anstice N (2018) Student acceptance of e-
learning methods in the laboratory class in optometry PLOS ONE 13(12) 1-15
httpsdoiorg101371journalpone0209004
Adewole-Odeshi E (2014) Attitude of students towards e-learning in South-West Nigerian universities An application of
technology acceptance model Library Philosophy and Practice Article 1035
Angolia M G amp Pagliari L R (2016) Factors for successful evolution and sustainability of quality distance education
Online Journal of Distance Learning Administration 19(3)
Ayele B A amp Birhanie W K (2018) Acceptance and use of e-learning systems The case of teachers in technology
institutes of Ethiopian universities Applied Informatics 5(1) 1-11 httpsdoiorg101186s40535-018-0048-7
Back D A von Malotky J Sostmann K Peters H Hube R amp Hoff E (2019) Experiences with using e-learning tools
in orthopedics in an uncontrolled field study application Orthopaedics amp Traumatology Surgery amp Research
105(2) 389-393 httpsdoiorg101016jotsr201901002
Bhardwaj A amp Goundar S (2018) Students perspective of elearning and the future of education with MOOCs
International Journal of Computer Engineering 7(5) 248-260
Bhattacherjee A (2012) Social science research Principles methods and practices Textbooks Collection
httpscholarcommonsusfeduoa_textbooks3
Bond M Mariacuten V I Dolch C Bedenlier S amp Zawacki-Ritcher O (2018) Digital transformation in German higher
education Student and teacher perceptions and usage of digital media International Journal of Educational
Technology in Higher Education 15(48) httpsdoiorg101186s41239-018-0130-1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 197
Braun V amp Clarke V (2006) Using thematic analysis in psychology Qualitative Research in Psychology 33 77-101
Chopra G Madan P Jaisingh P amp Bhaskar P (2019) Effectiveness of e-learning portal from studentsrsquo perspective A
structural equation model (SEM) approach Interactive Technology and Smart Education 16(2) 94-116
httpsdoiorg101108ITSE-05-2018-0027
Creswell J W (2014) Research Design Qualitative quantitative and mixed methods approaches (4th ed) Sage
Publications
Damanpour F amp Schneider M (2006) Phases of the adoption of innovation in organisations Effects of environment
organisation and top managers British Journal of Management 17 215ndash236 httpsdoiorg101111j1467-
8551200600498x
Davis F D (1989) Perceived usefulness perceived ease of use and user acceptance of information technology MIS
Quarterly 13(3) 319ndash340 httpsdoiorg102307249008
Drazin R amp Van de Ven A H (1985) Alternative forms of fit in contingency theory Administrative Science Quarterly
30(4) 514-539 httpsdoiorg1023072392695
Drent M amp Meelissen M (2008) Which factors obstruct or stimulate teacher educators to use ICT innovatively
Computers amp Education 51 187ndash199 httpsdoiorg101016jcompedu200705001
Eze S C Chinedu-Eze V C amp Bello A O (2018) The utilisation of e-learning facilities in the educational delivery
system of Nigeria A study of M-University International Journal of Educational Technology in Higher Education
15 (34) 1-20 httpsdoiorg101186s41239-018-0116-z
Ferreira A Teixeira A L amp Dantas A R (2015) Non-technological innovation activities mediate the impacts of the
intra- and extra-organisational contexts on technological innovation outputs Enterprise and Work Innovation
Studies 11 9-43
Gerasimova V G Melamud M R Tutaeva D R Romanova Y D amp Zhenova N A (2018) The adoption of e-learning
technology at the Faculty of Distance Learning of Plekhanov Russian University of Economics Journal of Social
Studies Education Research 9(2) 172-188
Glazier R A Hamann K Pollock P H amp B Wilson B M (2019) Age gender and student success Mixing face-to-face
and online courses in political science Journal of Political Science Education 16(2) 142-157 httpsdoiorg1010801551216920181515636
Greene J C Caracelli V J amp Graham W F (1989) Toward a conceptual framework for mixed method evaluation
designs Educational Evaluation and Policy Analysis 11(3) 255-274 httpsdoiorg1023071163620
Gwamba G Renken J Nampijja J Mayende G amp Muyinda P B (2018) Contextualisation of e-learning systems in
higher education institutions In M Auer amp T Tsiatsos (Eds) Interactive mobile communication technologies and
learning Proceedings of the 11th IMCL conference (pp 44-55) Springer
Hardaker G amp Singh G (2011) The adoption and diffusion of eLearning in UK universities A comparative case study
using Giddenss theory of structuration Campus-Wide Information Systems 28(4) 221ndash233
httpsdoiorg10110810650741111162707
Kim H J Hong A J amp Song H (2019) The roles of academic engagement and digital readiness in studentsrsquo
achievements in university e-learning environments International Journal of Educational Technology in Higher
Education 16(21) 1-18 httpsdoiorg101186s41239-019-0152-3
Kimiloglu H Ozturan M amp Kutlu B (2017) Perceptions about and attitude toward the usage of e-learning in corporate
training Computers in Human Behavior 72 339-349 httpsdoiorg101016jchb201702062
Kisanga D amp Ireson G (2015) Barriers and strategies on adoption of e-learning in Tanzanian higher learning institutions
Lessons for adopters International Journal of Education and Development using Information and Communication
Technology (IJEDICT) 11(2) 126-137
Lee Y-K amp Pituch K (2002 December 10ndash13) Moderators in the adoption of e-learning An investigation of the role of
gender [Article] The Second International Conference on Electronic Business Taipei Taiwan
Lippman P C (2010) Can the physical environment have an impact on the learning environment CELE Exchange
httpsdoiorg1017875km4g21wpwr1-en
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 198
Maina M K amp Nzuki D M (2015) Adoption determinants of e-learning management system in institutions of higher
learning in Kenya A case of selected universities in Nairobi metropolitan International Journal of Business and
Social Science 6(2) 233ndash248
Martin M (1991) The culture of the telephone In PD Hopkins (Ed) Sexmachine Readings in culture gender and
technology (pp 50-74) Indiana University Press
Moakofhi M Leteane O Phiri T Pholele T amp Sebalatlheng P (2017) Challenges of introducing e-learning at
Botswana University of Agriculture and Natural Resources Lecturersrsquo perspective International Journal of
Education and Development using ICT 13( 2) 4-20
Nabushawo H M Muyinda P B Isabwe G M N Prinz A amp Mayende G (2018) Improving online interaction among
blended distance learners at Makerere University In M E Auer D Guralnick amp I Simonics (Eds) Advances in
Intelligent Systems and Computing (pp 63-69) Springer httpsdoiorg101007978-3-319-73210-7_8
Odewumi M O Yusuf M O amp Oputa G O (2018) UTAUT model Intention to use social media for learning interactive
effect of postgraduate gender in South-West Nigeria International Journal of Education and Development using
Information and Communication Technology (IJEDICT) 14(3) 239-251
Okai-Ugbaje S Ardzejewska K amp Imran A (2020) Readiness roles and responsibilities of stakeholders for sustainable
mobile learning adoption in higher education Education Sciences 10(3) 49-69
httpsdoiorg103390educsci10030049
Ozkan S amp Koseler R (2009) Multi-dimensional studentsrsquo evaluation of e-learning systems in the higher education
context An empirical investigation Computers amp Education 53(4) 1285ndash1296
httpsdoiorg101016jcompedu200906011
Parlakkılıccedil A (2014) Change management in transition to e-learning system Qualitative and Quantitative Methods in
Libraries 3(3) 637ndash651
Pereira A Martins P Morgado L amp Fonseca B (2018) Technological proposal using virtual worlds to support
entrepreneurship education for primary school children In M E Auer D Guralnick amp I Simonics (Eds)
Advances in Intelligent Systems and Computing (pp 124-132) Springer
Ramiacuterez-Correa P E Arenas-Gaitaacuten J amp Rondaacuten-Cataluntildea F J (2015) Gender and acceptance of e-learning A multi-
group analysis based on a structural equation model among college students in Chile and Spain PLOS ONE
10(10) 1-17 httpsdoiorg101371journalpone0140460
Rhema A amp Miliszewska I (2014) Analysis of student attitudes towards e-learning The case of engineering students in
Libya Issues in Informing Science and Information Technology 11 169-190 httpsdoiorg10289451987
Rogers E M (2003) Diffusion of innovations (5th ed) Free Press
Salinas J (2004) Cambios metodoloacutegicos con las TIC Estrategias didaacutecticas y entornos virtuales de ensentildeanza-aprendizaje
Bordoacuten 56(3-4) 469-481
Selim H M (2007) Critical success factors for e-learning acceptance Confirmatory factor models Computers amp
Education 49(2) 396ndash413 httpsdoi101016jcompedu200509004
Shah M amp Cheng M (2019) Exploring factors impacting student engagement in open access courses Open learning The
Journal of Open Distance and E-Learning 34(2) 187-202 httpsdoiorg1010800268051320181508337
Singh G ODonoghue J amp Worton H (2005) A study into the effects of elearning on higher education Journal of
University Teaching and Learning Practice 2(1) 13-24
Tchamyou V S (2017) The role of knowledge economy in African business Journal of the Knowledge Economy 8(4)
1189ndash1228 httpsdoiorg101007s13132-016-0417-1
The M M amp Usagawa T (2018) A comparative study of studentsrsquo readiness on e-learning education between Indonesia
and Myanmar American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS) 40(1)
113-124
Venkatraman N (1989) The concept of fit in strategy research Toward verbal and statistical correspondence Academy of
Management Review 9(3) 513-525 httpsdoiorg102307258177
Zuvic-Butorac M Nebic Z amp Nemcanin D (2011) Establishing an institutional framework for an e-learning
implementation Experiences from the University of Rijeka Croatia Journal of Information Technology Education
Innovations in Practice 10 43-56 httpsdoiorg10289451364
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Recommended Citation
-
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Cover Page Footnote
-
- tmp1624440487pdfGS9c9
-
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 189
Factors Constructs Operationalization References
Interaction The interaction between the main factors
ie organization and the individual
affect each other
Drazine amp Van de Ven (1985)
Perception This is the studentrsquos perspective that
indicates whether the factors encourage
adoption or not
Gerasimova et al (2018)
Alignment Level of coherence Venkatraman (1989)
Adoption of TSL Intention to use innovative use and
acceptance of TSL
Rogers (2003) Davis (1989)
METHODOLOGICAL FRAMEWORK
To investigate the predictors of the successful adoption of TSL among students the quantitative survey
mixed and cross-sectional research designs were used (Creswell 2014 Greene et al 1989) A recent
study by Shah and Cheng (2019) carried out on studentsrsquo perceptions used a quantitative research
design Thus the same design was adopted for this study In quantitative designs surveys are usually
used The researchers used a survey to collect data from a total of 184 students The survey was
structured into four main parts background information adoption of TSL organizational and individual
factors Bhardwaj and Goundar (2018) in their study on studentsrsquo perceptions on TSL used a mixed
research approach The researchers adopted the said research approach whereby the largely quantitative
and little qualitative techniques were used
Besides lecturers the population of study included students from both Makerere and Gulu universities
Students were chosen because they are the main users of TSL (Bhardwaj amp Goundar 2018) and they are
faced with challenges in using this type of learning (Gerasimova et al 2018) Purposive and simple
random sampling were used for quantitative data The given universities were purposively chosen
because of the level of knowledge and use of TSL Simple random sampling was used at departmental
level to collect quantitative data from students of agricultural sciences because they are among the main
users of TSL facilities at this level Purposive homogeneous sampling was used for qualitative data A
total of six students were interviewed to complement the questionnaire data
The study took place at a particular point in time hence it was cross-sectional in nature Internal and
external validity checks were used (Bhattacherjee 2012) Internal validity was achieved by omitting
extraneous variables so that changes in the response to variables is caused by the hypothesized
explanatory variables External validity was achieved by generalizing from Makerere and Gulu
universities to other universities These two universities were chosen because their lecturers have been
motivated earlier their students would have had more exposure to the technology adoption and with that
experience it would be appropriate to capture their perspectives Validity of the student qualitative
instrument was achieved through use of research experts who were used to validate whether the content
in the instrument could get the data required (Ozkan amp Koseler 2009)
Additionally the developed question concepts were derived from past relevant studies This can be
related to Bhardwaj and Goundar (2019) who captured studentsrsquo perceptions on TSL based on the
modification of concepts from relevant past studies Studies on studentsrsquo perceptions taking a
quantitative approach are usually carried out using reliability tests Kim et al (2019) carried out a
reliability test on a questionnaire that was administered to undergraduate students in a university in
Korea using Cronbachrsquos alpha Similarly the researchers used the same alpha to test questions in the
student self-administered questionnaire The outcome variable of the adoption of TSL was
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 190
operationalized as intention to use innovative use and acceptance of TSL with Cronbach alphas of 064
067 070 respectively The organizational factors had a Cronbach alpha of 073 The researchers
followed ethics guidelines to accomplish the study
RESULTS AND ANALYSIS
Background Information
The majority (821) of the students were aged between 21 and 30 years old This is in line with
Bhardwaj and Goundar (2018) who indicated that the majority of the student respondents were between
21 to 30 years old The majority (641) of the student respondents were male while 359 were female
respondents This is in line with Zuvic-Butorac et al (2011) who found that female students
concentrated on art subjects while their male counterparts were in engineering natural science and ICT
Most (410) of the students were in their second year of study followed by first year students (ie
320) The majority of the students (ie 940) had access to email Few (386) students had laptops
This is because these students may not be in position to afford such devices Most (592) of the
respondents revealed that there are functional TSL laboratories in their universities Most of the students
(571) were affiliated to Gulu University For descriptive analysis of means and standard deviations
for selected research variables see Tables 2 and 3 All the data simulations were based on a Likert scale
of 5 Descriptive analysis of the individual (student) presenting modal age gender and level of education
of the whole population of students (ie N =184) is shown in Table 3
Descriptive Statistics
Table 2
Descriptive Statistics for Selected Research Variables (N =184)
Variable Brief Description of Variables M a Min Max SD
Adoption of TSL
Intention to Use
ITU1 Computers 445 1 5 0979
ITU2 CD-ROMs 283 1 5 1468
ITU3 Web-based learning 384 1 5 1344
ITU4 Video conferencing 359 1 5 1449
ITU5 University TSL environments eg Black-Board 366 1 5 1425
Innovative Use
INU1 I am able to expound on what lecturers have provided to me in class using
the Internet
379 1 5 1334
INU2 I am able to make presentations in text audio and visual 380 1 5 1424
INU3 I am able to communicate with other students through online discussions
emails wikis and WhatsApp
371 1 5 1496
Acceptance
ACC1 Computers 452 1 5 0941
ACC2 CD-ROMs 296 1 5 1536
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 191
Variable Brief Description of Variables M a Min Max SD
ACC3 Web-based learning 375 1 5 1388
ACC4 Video conferencing 359 1 5 1376
ACC5 University TSL environments eg Black-Board 361 1 5 1536
Organizational Factors
GUELP1 Goal of university TSL policy 297 1 5 1408
ATIEXICT1 Availability of time to experiment with ICT 322 1 5 1366
AFS1 Availability of financial support 273 1 5 1544
COMAN1 Commitment of management 304 1 5 1362
a A score of 350 indicates that the person has and there was ldquoeg intention to use TSL encouragement
on use of TSL facilities and ldquohindrance to the progress of TSL ISsrdquo on the five-point Likert scale of
1(Very little or no intention to use TSL encouragement on use of TSL facilities and hindrance to the
progress of TSL ISs ) and 5(Very much intention to use TSL greatest encouragement on use of TSL
facilities and very much hindrance to the progress of TSL ISs)
Students had lsquomuchrsquo intention to use TSL facilities For instance they had lsquomuchrsquo intention to use
computers (ITU1) The students had lsquomuchrsquo innovative use of TSL (for instance they were able to make
presentations in text audio and video INU2) They also indicated very much acceptance of TSL For
instance they had very much acceptance of computers (ACC1)
See Table 3 for most frequent characteristics of each individual in the whole student population (ie N
=184)
Table 3
Individual Factors (N = 184)
Individual Factors Rate of Occurrence Most Frequent
Individual Factors
AGE Most frequent age of students 25 Years
GEN Most frequent gender of students Male
LEDUC Most frequent year of study of students Year 2
Cluster Analyses
The researchers used the k-means clustering algorithm with the help of Statistica Software version 133
to generate six clusters The data were standardized Whereas several simulations were carried out (ie1
2 3 4 5 and 6) only the sixth simulation showed acceptable results All 6 simulations yielded p values
less than 005 (see Table 4) Table 4 indicates the measurement of the organizational factors and
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 192
adoption of TSL in universities in Uganda across the six student clusters Table 5 shows the
measurement of the individual factors across the said clusters
Table 4
Cluster Analysis and Analysis of Variance for Students
Cluster
Variable 1
(n = 37)
2
(n = 38)
3
(n = 19)
4
(n = 42)
5
(n = 24)
6
(n = 24)
ANOVA
F p
Adoption of TSL
Intention to Use TSL
ITU1 011 024 002 032 048 -161 244 00
ITU2 -007 -074 033 069 -014 -005 1109 00
ITU3 -101 037 035 058 039 -072 2502 00
ITU4 -084 031 031 059 031 -079 1893 00
ITU5 -056 022 -006 059 029 -078 1159 00
Innovative Use of TSL
INU1 -025 051 -024 065 -013 -122 2075 00
INU2 014 029 -142 049 052 -092 2671 00
INU3 -051 044 -128 061 049 -045 2449 00
Acceptance of TSL
ACC1 023 023 007 039 034 -179 3439 00
ACC2 -021 -085 050 092 018 -052 2579 00
ACC3 -087 041 007 064 033 -081 2219 00
ACC4 -100 027 029 067 057 -086 3169 00
ACC5 -065 001 -013 064 066 -069 1529 00
Organizational Factors
GUELP1 004 032 -024 078 -099 -075 2078 00
ATIEXICT1 019 -051 -069 089 -009 -040 1636 00
AFS1 012 -051 -044 105 -053 -036 2228 00
COMAN1 001 -017 -057 074 -018 -039 835 00
Note Positive values are indicated in bold while negative ones are not in bold
Table 5
Individual Factors per Cluster
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
AGE Most frequent
age of
students
26
Years
25
Years
25
Years
25
Years
26
Years
24
Years
356 00
GEN Most frequent
gender of
students
Male Equal
number
of male
and
female
Female Male Male Male 426 00
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 193
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
LEDUC Most frequent
year of
study of
students
Year 2 Year 2 Year 1 Year 2 Year 4 Year 1 409 00
Qualitative Analysis
Thematic analysis was used in analyzing qualitative data We used Braun and Clarke (2006)rsquos six
thematic analysis steps of familiarization generating initial codes searching reviewing defining and
naming themes and producing a report Studentsrsquo data comprised student interview data items from
which initial extracts were made Familiarization was carried out by reading and re-reading the said data
items Generating initial codes was achieved through capturing features of interest from the student data
set Searching was achieved through grouping student data relevant to potential themes Defining and
naming was achieved by categorizing the themes Finally a report about the student data was produced
The researchers used the most significant interview data that could support the quantitative results
presented in this paper in the discussion of findings section Thus the discussion of findings is
integrative
DISCUSSION OF FINDINGS
In this section qualitative findings have been integrated with the quantitative ones The letter lsquoSrsquo
denotes student Cluster 1 students were ranked third as far as the adoption of TSL is concerned because
of the quite weak alignment between the configurational factors For instance the students had no
intention to use web-based technology This was confirmed by student S5 who revealed that she did not
understand web-based learning These students could not interact with their colleagues using TSL
facilities Students in this cluster never embraced video conferencing technology because it is limited as
reflected in the main themes by the students S1 S3 and S5 However these students had the intention to
use computer technology This is consistent with student S1 who commented that ldquoI have the intention
to use computers for academic purposesrdquo They also had innovative use of TSL shown through their
ability to incorporate text audio and visual technology Furthermore these students accepted computer
technology This is supported by students S1 S2 and S6 who revealed that they use computers because
of the current education trend which demands them to be computer literate for academic purposes and
they are easy to work with
Further analysis of this cluster indicates that the organizational factors encourage these students to use
TSL facilities (see Table 4) Qualitative results from students S1 S4 and S3 respectively had the
following implications on the organizational factors
bull the goal of the TSL learning policy encourages the use of TSL facilities at a minimal level
bull students practise with ICT and also believe that the university indirectly supports them financially by
providing limited wireless fidelity
bull the university management is supportive by designing sessions on how to use computers
A typical student in this cluster was 26 years old male by gender and in his second year of study (see
Table 5) While these students have similar characteristics with those of Cluster 6 they have tried to
adopt TSL facilities compared Cluster 6 students because of their experience with such facilities
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 194
Cluster 2 students ranked second as far as adoption of TSL is concerned For example students in this
cluster revealed lsquomuchrsquo intention to use TSL For instance student S1 confirmed that ldquoWeb-based
learning offers more informationrdquo Students in this cluster were lsquovery muchrsquo capable of expounding on
what lecturers had provided to them in class using the Internet This was through ldquosurfingrdquo the Internet
using the Google search engine as revealed by student S1 Students in this cluster had lsquomuchrsquo
acceptance of TSL facilities such as web-based facilities This is because web-based learning can be
used for research work and expounding on what is taught in class by lecturers as revealed by student S1
This is confirmed by a recent study by Chopra et al (2019) that indicates that students are satisfied by
web-based technology
In relation to the organizational factors students in Cluster 2 agreed that the goal of university TSL
policy encourages their use of TSL facilities The qualitative results suggest that e-discussions can
compel students to use TSL facilities as revealed by Student S3 On average students in this cluster
were aged 25 years the number of male students was equivalent to that of female ones and they were in
their second year of study (see Table 5) These students could be better adopters than those of Cluster 1
because they seemed to have an equal gender distribution Such distribution may account for an unequal
educational technology use among Cluster 1 and 2 students who enjoyed a similar learning experience
(see Tables 4 and 5) Students of this cluster seemed to be better adopters than those of Clusters 1 3 5
and 6 because of their ability to make use of the TSL policy to their advantage (see Tables 4 and 5)
Cluster 3 students were low adopters of TSL because of low alignment between the configurational
factors thus ranked fifth as far as adoption of TSL is concerned These students lacked innovative use of
TSL facilities implying that these students cannot use such facilities to improve their learning
capabilities The same students however registered lsquovery muchrsquo acceptance of CD-ROMs (see Table 4)
This could be because this medium is a dependable way of accessing content by students (Kisanga amp
Ireson 2015)
Students in Cluster 3 perceived that the organizational factors never contributed to their use of TSL
facilities in any way (see Table 4) For example students had no time to experiment with ICT This
could be because students never practise with ICT due to the fact that the course is ldquohecticrdquo and the IT
laboratories are usually closed over the weekend as revealed by student S1 The average age gender
and level of education of a student in this cluster is 25 years female and first-year respectively (see
Table 5) These could be lower adopters of TSL than members of Clusters 2 and 5 because of their
gender Female respondents are disadvantaged when it comes to the use of information technology
(Odewumi 2018) Another plausible reason for the low adoption levels in Cluster 3 compared to those
in Clusters 2 and 1 could be the lack of innovative use of TSL (see Table 4)
Cluster 4 students were the greatest adopters of TSL among the six clusters This is because they had the
lsquogreatestrsquo alignment between the configurational factors These students are eager to use ICT innovative
and embraced TSL They are eager to use CD-ROM technology because such technology is cheap and
stores information as confirmed by students S1 and S6 They can innovatively expound on what
lectures have provided to them in class using the Internet with the help of search engines (such as
Google) as indicated by student S1 They have embraced video conference technology Students S1 S3
and S5 confirmed that they were able to imitate the limited video conferencing learning using the
WhatsApp facility
Students in Cluster 4 perceived that the organizational factors encouraged their use of TSL facilities
High scores were registered on the goal of the university TSL policy time to experiment with ICT
financial support and commitment of university management For instance during the interview process
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 195
student S3 revealed that ldquoa discussion policy for example may improve adoption of [TSL] because
once e-discussions are made they can compel one to use the [TSL] facilitiesrdquo The result from the
interview process on time to experiment with TSL conflicts with the cluster one whereby the majority
of the students never found time to practise with TSL facilities Shah and Cheng (2019) however
indicate that time influences the adoption of TSL facilities Quantitative findings in this cluster on
financial support could be related to those of student S3 who indicated that there was indirect financial
support by their university through the provision of wireless technology On the issue of management
commitment findings are in line with those of student S4 who felt that university management was
committed because they designed computer literacy sessions for them A typical student in this cluster
was 25 years old male by gender and in year 2 of study (see Table 5) This cluster (n = 42) had the
majority of the student respondents among the six clusters
The alignment of the configurational factors in Cluster 5 seemed to be lsquoweakerrsquo than that of Cluster 1
thus this cluster was ranked fourth Whereas the students in this cluster indicated lsquovery muchrsquo adoption
of TSL in some instances the configurational variables registered low scores For instance they had
very much acceptance of TSL environments yet they seemed not to be familiar with the TSL policy
The result on acceptance of TSL environments is parallel to that of Bond et al (2018) who indicated that
such environments are commonly used by students in higher education institutions in Germany The
result on the TSL policy was confirmed by student S4 who revealed that the TSL policy is not
effectively implemented in the university A normal student in this cluster was 26 years old male by
gender and in year 4 of the study (see Table 5) These students could be better adopters of TSL than
those of Clusters 3 and 6 because of their long-time experience with TSL as reflected in their year of
study compared to the said clusters (see Tables 4 and 5) It is not surprising this cluster had the best
distributions of ICTs among students
Similar to Cluster 5 Cluster 6 had 24 respondents (see Table 4) However students in this cluster are
coincidentally ranked as non-adopters of TSL among the six clusters (see Tables 4 and 5) This is
because there is no alignment between the configurational factors resulting in no adoption of TSL
These students were not willing to use IT could not modify their learning capabilities using IT and had
not realised the value of IT tools All 24 respondents in this cluster lsquoconcurredrsquo that the organization
never encouraged their use of TSL facilities This could imply that students were not involved at all
during the adoption of TSL Shah and Cheng (2019) reveal that students perceive that juggling work and
study caring for children financial difficulty and academic writing among other factors affect their
ability to adopt TSL On average students in this cluster were 26 years old male by gender and in year
1 of their study Being in their first year of study could imply that they had little experience with TSL
CONCLUSION
Identification of predictors of successful adoption of TSL among students was achieved using the
Gestalts approach Students perceived that organizational and individual factors predict successful
adoption of TSL Cluster 4 is the most coherent and as such adopted TSL most This is because the
organizational and individual factors were most aligned For example when students in this cluster are
financially supported and are in their second year of study they are eager to use to be innovative with
and embrace TSL And because of their eagerness innovativeness and ability to embrace TSL they have
accumulated more experience than others Cluster 6 students are non-adopters because they are more
inexperienced with TSL than the rest of the students
There seems to be a gap in the use of the non-linear techniques (eg clustering technique) in studies on
studentsrsquo perceptions Most studies for instance Chopra et al (2019) Gerasimova et al (2018) and Shah
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 196
and Cheng (2019) who have measured student perceptions have used linear techniques Thus this study
has closed this gap This study is a benchmark for universities in developing economies to integrate TSL
at university level For instance it should be noted that in order to achieve successful adoption of TSL
among students in universities management must be involved Nabushawo et al (2018) suggest that the
commitment of management can be achieved by collaborating with and training the users of TSL ISs
Since the world is challenged by Corona Virus Disease (COVID) this study can be used as model to
avail learning materials to students without spreading this disease
It should be noted that the rate of adoption of TSL among students is still low yet they have advanced in
age This contradicts Pereira et al (2018) who indicated that adoption of TSL usually takes place at an
early age It is therefore recommended that students should be supported to adopt TSL during their
earlier career years so that universities in Uganda can benefit from this innovation This can be done by
introducing TSL at primary level Universities need to strengthen their management capabilities such as
increasing the time studentsrsquo have to experiment with ICTs Further research is required to develop
strategies that can be adopted to enhance adoption of TSL among students at earlier ages Although this
study was carried out at a particular point in time it can also be carried out longitudinally There are
many indicators of the organization individual (student) and adoption of TSL besides those presented in
the conceptual framework Further research can be carried out on those Besides organization and
individual factors there is need to know the role of other factors in the adoption of TSL among students
While students from only two public universities were considered for this study students from other
universities can be considered as well
ACKNOWLEDGMENTS
The researchers want to thank the Almighty God for the gift of knowledge wisdom and understanding
in the writing of this paper The researchers also thank the Organization for Women in Science for the
Developing World (OWSD) and the Swedish International Development Agency (SIDA) for their
financial support in carrying out the study
REFERENCES
Acosta M L Sisley A Ross J Brailsford I Bhargava A Jacobs R amp Anstice N (2018) Student acceptance of e-
learning methods in the laboratory class in optometry PLOS ONE 13(12) 1-15
httpsdoiorg101371journalpone0209004
Adewole-Odeshi E (2014) Attitude of students towards e-learning in South-West Nigerian universities An application of
technology acceptance model Library Philosophy and Practice Article 1035
Angolia M G amp Pagliari L R (2016) Factors for successful evolution and sustainability of quality distance education
Online Journal of Distance Learning Administration 19(3)
Ayele B A amp Birhanie W K (2018) Acceptance and use of e-learning systems The case of teachers in technology
institutes of Ethiopian universities Applied Informatics 5(1) 1-11 httpsdoiorg101186s40535-018-0048-7
Back D A von Malotky J Sostmann K Peters H Hube R amp Hoff E (2019) Experiences with using e-learning tools
in orthopedics in an uncontrolled field study application Orthopaedics amp Traumatology Surgery amp Research
105(2) 389-393 httpsdoiorg101016jotsr201901002
Bhardwaj A amp Goundar S (2018) Students perspective of elearning and the future of education with MOOCs
International Journal of Computer Engineering 7(5) 248-260
Bhattacherjee A (2012) Social science research Principles methods and practices Textbooks Collection
httpscholarcommonsusfeduoa_textbooks3
Bond M Mariacuten V I Dolch C Bedenlier S amp Zawacki-Ritcher O (2018) Digital transformation in German higher
education Student and teacher perceptions and usage of digital media International Journal of Educational
Technology in Higher Education 15(48) httpsdoiorg101186s41239-018-0130-1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 197
Braun V amp Clarke V (2006) Using thematic analysis in psychology Qualitative Research in Psychology 33 77-101
Chopra G Madan P Jaisingh P amp Bhaskar P (2019) Effectiveness of e-learning portal from studentsrsquo perspective A
structural equation model (SEM) approach Interactive Technology and Smart Education 16(2) 94-116
httpsdoiorg101108ITSE-05-2018-0027
Creswell J W (2014) Research Design Qualitative quantitative and mixed methods approaches (4th ed) Sage
Publications
Damanpour F amp Schneider M (2006) Phases of the adoption of innovation in organisations Effects of environment
organisation and top managers British Journal of Management 17 215ndash236 httpsdoiorg101111j1467-
8551200600498x
Davis F D (1989) Perceived usefulness perceived ease of use and user acceptance of information technology MIS
Quarterly 13(3) 319ndash340 httpsdoiorg102307249008
Drazin R amp Van de Ven A H (1985) Alternative forms of fit in contingency theory Administrative Science Quarterly
30(4) 514-539 httpsdoiorg1023072392695
Drent M amp Meelissen M (2008) Which factors obstruct or stimulate teacher educators to use ICT innovatively
Computers amp Education 51 187ndash199 httpsdoiorg101016jcompedu200705001
Eze S C Chinedu-Eze V C amp Bello A O (2018) The utilisation of e-learning facilities in the educational delivery
system of Nigeria A study of M-University International Journal of Educational Technology in Higher Education
15 (34) 1-20 httpsdoiorg101186s41239-018-0116-z
Ferreira A Teixeira A L amp Dantas A R (2015) Non-technological innovation activities mediate the impacts of the
intra- and extra-organisational contexts on technological innovation outputs Enterprise and Work Innovation
Studies 11 9-43
Gerasimova V G Melamud M R Tutaeva D R Romanova Y D amp Zhenova N A (2018) The adoption of e-learning
technology at the Faculty of Distance Learning of Plekhanov Russian University of Economics Journal of Social
Studies Education Research 9(2) 172-188
Glazier R A Hamann K Pollock P H amp B Wilson B M (2019) Age gender and student success Mixing face-to-face
and online courses in political science Journal of Political Science Education 16(2) 142-157 httpsdoiorg1010801551216920181515636
Greene J C Caracelli V J amp Graham W F (1989) Toward a conceptual framework for mixed method evaluation
designs Educational Evaluation and Policy Analysis 11(3) 255-274 httpsdoiorg1023071163620
Gwamba G Renken J Nampijja J Mayende G amp Muyinda P B (2018) Contextualisation of e-learning systems in
higher education institutions In M Auer amp T Tsiatsos (Eds) Interactive mobile communication technologies and
learning Proceedings of the 11th IMCL conference (pp 44-55) Springer
Hardaker G amp Singh G (2011) The adoption and diffusion of eLearning in UK universities A comparative case study
using Giddenss theory of structuration Campus-Wide Information Systems 28(4) 221ndash233
httpsdoiorg10110810650741111162707
Kim H J Hong A J amp Song H (2019) The roles of academic engagement and digital readiness in studentsrsquo
achievements in university e-learning environments International Journal of Educational Technology in Higher
Education 16(21) 1-18 httpsdoiorg101186s41239-019-0152-3
Kimiloglu H Ozturan M amp Kutlu B (2017) Perceptions about and attitude toward the usage of e-learning in corporate
training Computers in Human Behavior 72 339-349 httpsdoiorg101016jchb201702062
Kisanga D amp Ireson G (2015) Barriers and strategies on adoption of e-learning in Tanzanian higher learning institutions
Lessons for adopters International Journal of Education and Development using Information and Communication
Technology (IJEDICT) 11(2) 126-137
Lee Y-K amp Pituch K (2002 December 10ndash13) Moderators in the adoption of e-learning An investigation of the role of
gender [Article] The Second International Conference on Electronic Business Taipei Taiwan
Lippman P C (2010) Can the physical environment have an impact on the learning environment CELE Exchange
httpsdoiorg1017875km4g21wpwr1-en
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 198
Maina M K amp Nzuki D M (2015) Adoption determinants of e-learning management system in institutions of higher
learning in Kenya A case of selected universities in Nairobi metropolitan International Journal of Business and
Social Science 6(2) 233ndash248
Martin M (1991) The culture of the telephone In PD Hopkins (Ed) Sexmachine Readings in culture gender and
technology (pp 50-74) Indiana University Press
Moakofhi M Leteane O Phiri T Pholele T amp Sebalatlheng P (2017) Challenges of introducing e-learning at
Botswana University of Agriculture and Natural Resources Lecturersrsquo perspective International Journal of
Education and Development using ICT 13( 2) 4-20
Nabushawo H M Muyinda P B Isabwe G M N Prinz A amp Mayende G (2018) Improving online interaction among
blended distance learners at Makerere University In M E Auer D Guralnick amp I Simonics (Eds) Advances in
Intelligent Systems and Computing (pp 63-69) Springer httpsdoiorg101007978-3-319-73210-7_8
Odewumi M O Yusuf M O amp Oputa G O (2018) UTAUT model Intention to use social media for learning interactive
effect of postgraduate gender in South-West Nigeria International Journal of Education and Development using
Information and Communication Technology (IJEDICT) 14(3) 239-251
Okai-Ugbaje S Ardzejewska K amp Imran A (2020) Readiness roles and responsibilities of stakeholders for sustainable
mobile learning adoption in higher education Education Sciences 10(3) 49-69
httpsdoiorg103390educsci10030049
Ozkan S amp Koseler R (2009) Multi-dimensional studentsrsquo evaluation of e-learning systems in the higher education
context An empirical investigation Computers amp Education 53(4) 1285ndash1296
httpsdoiorg101016jcompedu200906011
Parlakkılıccedil A (2014) Change management in transition to e-learning system Qualitative and Quantitative Methods in
Libraries 3(3) 637ndash651
Pereira A Martins P Morgado L amp Fonseca B (2018) Technological proposal using virtual worlds to support
entrepreneurship education for primary school children In M E Auer D Guralnick amp I Simonics (Eds)
Advances in Intelligent Systems and Computing (pp 124-132) Springer
Ramiacuterez-Correa P E Arenas-Gaitaacuten J amp Rondaacuten-Cataluntildea F J (2015) Gender and acceptance of e-learning A multi-
group analysis based on a structural equation model among college students in Chile and Spain PLOS ONE
10(10) 1-17 httpsdoiorg101371journalpone0140460
Rhema A amp Miliszewska I (2014) Analysis of student attitudes towards e-learning The case of engineering students in
Libya Issues in Informing Science and Information Technology 11 169-190 httpsdoiorg10289451987
Rogers E M (2003) Diffusion of innovations (5th ed) Free Press
Salinas J (2004) Cambios metodoloacutegicos con las TIC Estrategias didaacutecticas y entornos virtuales de ensentildeanza-aprendizaje
Bordoacuten 56(3-4) 469-481
Selim H M (2007) Critical success factors for e-learning acceptance Confirmatory factor models Computers amp
Education 49(2) 396ndash413 httpsdoi101016jcompedu200509004
Shah M amp Cheng M (2019) Exploring factors impacting student engagement in open access courses Open learning The
Journal of Open Distance and E-Learning 34(2) 187-202 httpsdoiorg1010800268051320181508337
Singh G ODonoghue J amp Worton H (2005) A study into the effects of elearning on higher education Journal of
University Teaching and Learning Practice 2(1) 13-24
Tchamyou V S (2017) The role of knowledge economy in African business Journal of the Knowledge Economy 8(4)
1189ndash1228 httpsdoiorg101007s13132-016-0417-1
The M M amp Usagawa T (2018) A comparative study of studentsrsquo readiness on e-learning education between Indonesia
and Myanmar American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS) 40(1)
113-124
Venkatraman N (1989) The concept of fit in strategy research Toward verbal and statistical correspondence Academy of
Management Review 9(3) 513-525 httpsdoiorg102307258177
Zuvic-Butorac M Nebic Z amp Nemcanin D (2011) Establishing an institutional framework for an e-learning
implementation Experiences from the University of Rijeka Croatia Journal of Information Technology Education
Innovations in Practice 10 43-56 httpsdoiorg10289451364
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Recommended Citation
-
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Cover Page Footnote
-
- tmp1624440487pdfGS9c9
-
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 190
operationalized as intention to use innovative use and acceptance of TSL with Cronbach alphas of 064
067 070 respectively The organizational factors had a Cronbach alpha of 073 The researchers
followed ethics guidelines to accomplish the study
RESULTS AND ANALYSIS
Background Information
The majority (821) of the students were aged between 21 and 30 years old This is in line with
Bhardwaj and Goundar (2018) who indicated that the majority of the student respondents were between
21 to 30 years old The majority (641) of the student respondents were male while 359 were female
respondents This is in line with Zuvic-Butorac et al (2011) who found that female students
concentrated on art subjects while their male counterparts were in engineering natural science and ICT
Most (410) of the students were in their second year of study followed by first year students (ie
320) The majority of the students (ie 940) had access to email Few (386) students had laptops
This is because these students may not be in position to afford such devices Most (592) of the
respondents revealed that there are functional TSL laboratories in their universities Most of the students
(571) were affiliated to Gulu University For descriptive analysis of means and standard deviations
for selected research variables see Tables 2 and 3 All the data simulations were based on a Likert scale
of 5 Descriptive analysis of the individual (student) presenting modal age gender and level of education
of the whole population of students (ie N =184) is shown in Table 3
Descriptive Statistics
Table 2
Descriptive Statistics for Selected Research Variables (N =184)
Variable Brief Description of Variables M a Min Max SD
Adoption of TSL
Intention to Use
ITU1 Computers 445 1 5 0979
ITU2 CD-ROMs 283 1 5 1468
ITU3 Web-based learning 384 1 5 1344
ITU4 Video conferencing 359 1 5 1449
ITU5 University TSL environments eg Black-Board 366 1 5 1425
Innovative Use
INU1 I am able to expound on what lecturers have provided to me in class using
the Internet
379 1 5 1334
INU2 I am able to make presentations in text audio and visual 380 1 5 1424
INU3 I am able to communicate with other students through online discussions
emails wikis and WhatsApp
371 1 5 1496
Acceptance
ACC1 Computers 452 1 5 0941
ACC2 CD-ROMs 296 1 5 1536
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 191
Variable Brief Description of Variables M a Min Max SD
ACC3 Web-based learning 375 1 5 1388
ACC4 Video conferencing 359 1 5 1376
ACC5 University TSL environments eg Black-Board 361 1 5 1536
Organizational Factors
GUELP1 Goal of university TSL policy 297 1 5 1408
ATIEXICT1 Availability of time to experiment with ICT 322 1 5 1366
AFS1 Availability of financial support 273 1 5 1544
COMAN1 Commitment of management 304 1 5 1362
a A score of 350 indicates that the person has and there was ldquoeg intention to use TSL encouragement
on use of TSL facilities and ldquohindrance to the progress of TSL ISsrdquo on the five-point Likert scale of
1(Very little or no intention to use TSL encouragement on use of TSL facilities and hindrance to the
progress of TSL ISs ) and 5(Very much intention to use TSL greatest encouragement on use of TSL
facilities and very much hindrance to the progress of TSL ISs)
Students had lsquomuchrsquo intention to use TSL facilities For instance they had lsquomuchrsquo intention to use
computers (ITU1) The students had lsquomuchrsquo innovative use of TSL (for instance they were able to make
presentations in text audio and video INU2) They also indicated very much acceptance of TSL For
instance they had very much acceptance of computers (ACC1)
See Table 3 for most frequent characteristics of each individual in the whole student population (ie N
=184)
Table 3
Individual Factors (N = 184)
Individual Factors Rate of Occurrence Most Frequent
Individual Factors
AGE Most frequent age of students 25 Years
GEN Most frequent gender of students Male
LEDUC Most frequent year of study of students Year 2
Cluster Analyses
The researchers used the k-means clustering algorithm with the help of Statistica Software version 133
to generate six clusters The data were standardized Whereas several simulations were carried out (ie1
2 3 4 5 and 6) only the sixth simulation showed acceptable results All 6 simulations yielded p values
less than 005 (see Table 4) Table 4 indicates the measurement of the organizational factors and
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 192
adoption of TSL in universities in Uganda across the six student clusters Table 5 shows the
measurement of the individual factors across the said clusters
Table 4
Cluster Analysis and Analysis of Variance for Students
Cluster
Variable 1
(n = 37)
2
(n = 38)
3
(n = 19)
4
(n = 42)
5
(n = 24)
6
(n = 24)
ANOVA
F p
Adoption of TSL
Intention to Use TSL
ITU1 011 024 002 032 048 -161 244 00
ITU2 -007 -074 033 069 -014 -005 1109 00
ITU3 -101 037 035 058 039 -072 2502 00
ITU4 -084 031 031 059 031 -079 1893 00
ITU5 -056 022 -006 059 029 -078 1159 00
Innovative Use of TSL
INU1 -025 051 -024 065 -013 -122 2075 00
INU2 014 029 -142 049 052 -092 2671 00
INU3 -051 044 -128 061 049 -045 2449 00
Acceptance of TSL
ACC1 023 023 007 039 034 -179 3439 00
ACC2 -021 -085 050 092 018 -052 2579 00
ACC3 -087 041 007 064 033 -081 2219 00
ACC4 -100 027 029 067 057 -086 3169 00
ACC5 -065 001 -013 064 066 -069 1529 00
Organizational Factors
GUELP1 004 032 -024 078 -099 -075 2078 00
ATIEXICT1 019 -051 -069 089 -009 -040 1636 00
AFS1 012 -051 -044 105 -053 -036 2228 00
COMAN1 001 -017 -057 074 -018 -039 835 00
Note Positive values are indicated in bold while negative ones are not in bold
Table 5
Individual Factors per Cluster
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
AGE Most frequent
age of
students
26
Years
25
Years
25
Years
25
Years
26
Years
24
Years
356 00
GEN Most frequent
gender of
students
Male Equal
number
of male
and
female
Female Male Male Male 426 00
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 193
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
LEDUC Most frequent
year of
study of
students
Year 2 Year 2 Year 1 Year 2 Year 4 Year 1 409 00
Qualitative Analysis
Thematic analysis was used in analyzing qualitative data We used Braun and Clarke (2006)rsquos six
thematic analysis steps of familiarization generating initial codes searching reviewing defining and
naming themes and producing a report Studentsrsquo data comprised student interview data items from
which initial extracts were made Familiarization was carried out by reading and re-reading the said data
items Generating initial codes was achieved through capturing features of interest from the student data
set Searching was achieved through grouping student data relevant to potential themes Defining and
naming was achieved by categorizing the themes Finally a report about the student data was produced
The researchers used the most significant interview data that could support the quantitative results
presented in this paper in the discussion of findings section Thus the discussion of findings is
integrative
DISCUSSION OF FINDINGS
In this section qualitative findings have been integrated with the quantitative ones The letter lsquoSrsquo
denotes student Cluster 1 students were ranked third as far as the adoption of TSL is concerned because
of the quite weak alignment between the configurational factors For instance the students had no
intention to use web-based technology This was confirmed by student S5 who revealed that she did not
understand web-based learning These students could not interact with their colleagues using TSL
facilities Students in this cluster never embraced video conferencing technology because it is limited as
reflected in the main themes by the students S1 S3 and S5 However these students had the intention to
use computer technology This is consistent with student S1 who commented that ldquoI have the intention
to use computers for academic purposesrdquo They also had innovative use of TSL shown through their
ability to incorporate text audio and visual technology Furthermore these students accepted computer
technology This is supported by students S1 S2 and S6 who revealed that they use computers because
of the current education trend which demands them to be computer literate for academic purposes and
they are easy to work with
Further analysis of this cluster indicates that the organizational factors encourage these students to use
TSL facilities (see Table 4) Qualitative results from students S1 S4 and S3 respectively had the
following implications on the organizational factors
bull the goal of the TSL learning policy encourages the use of TSL facilities at a minimal level
bull students practise with ICT and also believe that the university indirectly supports them financially by
providing limited wireless fidelity
bull the university management is supportive by designing sessions on how to use computers
A typical student in this cluster was 26 years old male by gender and in his second year of study (see
Table 5) While these students have similar characteristics with those of Cluster 6 they have tried to
adopt TSL facilities compared Cluster 6 students because of their experience with such facilities
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 194
Cluster 2 students ranked second as far as adoption of TSL is concerned For example students in this
cluster revealed lsquomuchrsquo intention to use TSL For instance student S1 confirmed that ldquoWeb-based
learning offers more informationrdquo Students in this cluster were lsquovery muchrsquo capable of expounding on
what lecturers had provided to them in class using the Internet This was through ldquosurfingrdquo the Internet
using the Google search engine as revealed by student S1 Students in this cluster had lsquomuchrsquo
acceptance of TSL facilities such as web-based facilities This is because web-based learning can be
used for research work and expounding on what is taught in class by lecturers as revealed by student S1
This is confirmed by a recent study by Chopra et al (2019) that indicates that students are satisfied by
web-based technology
In relation to the organizational factors students in Cluster 2 agreed that the goal of university TSL
policy encourages their use of TSL facilities The qualitative results suggest that e-discussions can
compel students to use TSL facilities as revealed by Student S3 On average students in this cluster
were aged 25 years the number of male students was equivalent to that of female ones and they were in
their second year of study (see Table 5) These students could be better adopters than those of Cluster 1
because they seemed to have an equal gender distribution Such distribution may account for an unequal
educational technology use among Cluster 1 and 2 students who enjoyed a similar learning experience
(see Tables 4 and 5) Students of this cluster seemed to be better adopters than those of Clusters 1 3 5
and 6 because of their ability to make use of the TSL policy to their advantage (see Tables 4 and 5)
Cluster 3 students were low adopters of TSL because of low alignment between the configurational
factors thus ranked fifth as far as adoption of TSL is concerned These students lacked innovative use of
TSL facilities implying that these students cannot use such facilities to improve their learning
capabilities The same students however registered lsquovery muchrsquo acceptance of CD-ROMs (see Table 4)
This could be because this medium is a dependable way of accessing content by students (Kisanga amp
Ireson 2015)
Students in Cluster 3 perceived that the organizational factors never contributed to their use of TSL
facilities in any way (see Table 4) For example students had no time to experiment with ICT This
could be because students never practise with ICT due to the fact that the course is ldquohecticrdquo and the IT
laboratories are usually closed over the weekend as revealed by student S1 The average age gender
and level of education of a student in this cluster is 25 years female and first-year respectively (see
Table 5) These could be lower adopters of TSL than members of Clusters 2 and 5 because of their
gender Female respondents are disadvantaged when it comes to the use of information technology
(Odewumi 2018) Another plausible reason for the low adoption levels in Cluster 3 compared to those
in Clusters 2 and 1 could be the lack of innovative use of TSL (see Table 4)
Cluster 4 students were the greatest adopters of TSL among the six clusters This is because they had the
lsquogreatestrsquo alignment between the configurational factors These students are eager to use ICT innovative
and embraced TSL They are eager to use CD-ROM technology because such technology is cheap and
stores information as confirmed by students S1 and S6 They can innovatively expound on what
lectures have provided to them in class using the Internet with the help of search engines (such as
Google) as indicated by student S1 They have embraced video conference technology Students S1 S3
and S5 confirmed that they were able to imitate the limited video conferencing learning using the
WhatsApp facility
Students in Cluster 4 perceived that the organizational factors encouraged their use of TSL facilities
High scores were registered on the goal of the university TSL policy time to experiment with ICT
financial support and commitment of university management For instance during the interview process
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 195
student S3 revealed that ldquoa discussion policy for example may improve adoption of [TSL] because
once e-discussions are made they can compel one to use the [TSL] facilitiesrdquo The result from the
interview process on time to experiment with TSL conflicts with the cluster one whereby the majority
of the students never found time to practise with TSL facilities Shah and Cheng (2019) however
indicate that time influences the adoption of TSL facilities Quantitative findings in this cluster on
financial support could be related to those of student S3 who indicated that there was indirect financial
support by their university through the provision of wireless technology On the issue of management
commitment findings are in line with those of student S4 who felt that university management was
committed because they designed computer literacy sessions for them A typical student in this cluster
was 25 years old male by gender and in year 2 of study (see Table 5) This cluster (n = 42) had the
majority of the student respondents among the six clusters
The alignment of the configurational factors in Cluster 5 seemed to be lsquoweakerrsquo than that of Cluster 1
thus this cluster was ranked fourth Whereas the students in this cluster indicated lsquovery muchrsquo adoption
of TSL in some instances the configurational variables registered low scores For instance they had
very much acceptance of TSL environments yet they seemed not to be familiar with the TSL policy
The result on acceptance of TSL environments is parallel to that of Bond et al (2018) who indicated that
such environments are commonly used by students in higher education institutions in Germany The
result on the TSL policy was confirmed by student S4 who revealed that the TSL policy is not
effectively implemented in the university A normal student in this cluster was 26 years old male by
gender and in year 4 of the study (see Table 5) These students could be better adopters of TSL than
those of Clusters 3 and 6 because of their long-time experience with TSL as reflected in their year of
study compared to the said clusters (see Tables 4 and 5) It is not surprising this cluster had the best
distributions of ICTs among students
Similar to Cluster 5 Cluster 6 had 24 respondents (see Table 4) However students in this cluster are
coincidentally ranked as non-adopters of TSL among the six clusters (see Tables 4 and 5) This is
because there is no alignment between the configurational factors resulting in no adoption of TSL
These students were not willing to use IT could not modify their learning capabilities using IT and had
not realised the value of IT tools All 24 respondents in this cluster lsquoconcurredrsquo that the organization
never encouraged their use of TSL facilities This could imply that students were not involved at all
during the adoption of TSL Shah and Cheng (2019) reveal that students perceive that juggling work and
study caring for children financial difficulty and academic writing among other factors affect their
ability to adopt TSL On average students in this cluster were 26 years old male by gender and in year
1 of their study Being in their first year of study could imply that they had little experience with TSL
CONCLUSION
Identification of predictors of successful adoption of TSL among students was achieved using the
Gestalts approach Students perceived that organizational and individual factors predict successful
adoption of TSL Cluster 4 is the most coherent and as such adopted TSL most This is because the
organizational and individual factors were most aligned For example when students in this cluster are
financially supported and are in their second year of study they are eager to use to be innovative with
and embrace TSL And because of their eagerness innovativeness and ability to embrace TSL they have
accumulated more experience than others Cluster 6 students are non-adopters because they are more
inexperienced with TSL than the rest of the students
There seems to be a gap in the use of the non-linear techniques (eg clustering technique) in studies on
studentsrsquo perceptions Most studies for instance Chopra et al (2019) Gerasimova et al (2018) and Shah
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 196
and Cheng (2019) who have measured student perceptions have used linear techniques Thus this study
has closed this gap This study is a benchmark for universities in developing economies to integrate TSL
at university level For instance it should be noted that in order to achieve successful adoption of TSL
among students in universities management must be involved Nabushawo et al (2018) suggest that the
commitment of management can be achieved by collaborating with and training the users of TSL ISs
Since the world is challenged by Corona Virus Disease (COVID) this study can be used as model to
avail learning materials to students without spreading this disease
It should be noted that the rate of adoption of TSL among students is still low yet they have advanced in
age This contradicts Pereira et al (2018) who indicated that adoption of TSL usually takes place at an
early age It is therefore recommended that students should be supported to adopt TSL during their
earlier career years so that universities in Uganda can benefit from this innovation This can be done by
introducing TSL at primary level Universities need to strengthen their management capabilities such as
increasing the time studentsrsquo have to experiment with ICTs Further research is required to develop
strategies that can be adopted to enhance adoption of TSL among students at earlier ages Although this
study was carried out at a particular point in time it can also be carried out longitudinally There are
many indicators of the organization individual (student) and adoption of TSL besides those presented in
the conceptual framework Further research can be carried out on those Besides organization and
individual factors there is need to know the role of other factors in the adoption of TSL among students
While students from only two public universities were considered for this study students from other
universities can be considered as well
ACKNOWLEDGMENTS
The researchers want to thank the Almighty God for the gift of knowledge wisdom and understanding
in the writing of this paper The researchers also thank the Organization for Women in Science for the
Developing World (OWSD) and the Swedish International Development Agency (SIDA) for their
financial support in carrying out the study
REFERENCES
Acosta M L Sisley A Ross J Brailsford I Bhargava A Jacobs R amp Anstice N (2018) Student acceptance of e-
learning methods in the laboratory class in optometry PLOS ONE 13(12) 1-15
httpsdoiorg101371journalpone0209004
Adewole-Odeshi E (2014) Attitude of students towards e-learning in South-West Nigerian universities An application of
technology acceptance model Library Philosophy and Practice Article 1035
Angolia M G amp Pagliari L R (2016) Factors for successful evolution and sustainability of quality distance education
Online Journal of Distance Learning Administration 19(3)
Ayele B A amp Birhanie W K (2018) Acceptance and use of e-learning systems The case of teachers in technology
institutes of Ethiopian universities Applied Informatics 5(1) 1-11 httpsdoiorg101186s40535-018-0048-7
Back D A von Malotky J Sostmann K Peters H Hube R amp Hoff E (2019) Experiences with using e-learning tools
in orthopedics in an uncontrolled field study application Orthopaedics amp Traumatology Surgery amp Research
105(2) 389-393 httpsdoiorg101016jotsr201901002
Bhardwaj A amp Goundar S (2018) Students perspective of elearning and the future of education with MOOCs
International Journal of Computer Engineering 7(5) 248-260
Bhattacherjee A (2012) Social science research Principles methods and practices Textbooks Collection
httpscholarcommonsusfeduoa_textbooks3
Bond M Mariacuten V I Dolch C Bedenlier S amp Zawacki-Ritcher O (2018) Digital transformation in German higher
education Student and teacher perceptions and usage of digital media International Journal of Educational
Technology in Higher Education 15(48) httpsdoiorg101186s41239-018-0130-1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 197
Braun V amp Clarke V (2006) Using thematic analysis in psychology Qualitative Research in Psychology 33 77-101
Chopra G Madan P Jaisingh P amp Bhaskar P (2019) Effectiveness of e-learning portal from studentsrsquo perspective A
structural equation model (SEM) approach Interactive Technology and Smart Education 16(2) 94-116
httpsdoiorg101108ITSE-05-2018-0027
Creswell J W (2014) Research Design Qualitative quantitative and mixed methods approaches (4th ed) Sage
Publications
Damanpour F amp Schneider M (2006) Phases of the adoption of innovation in organisations Effects of environment
organisation and top managers British Journal of Management 17 215ndash236 httpsdoiorg101111j1467-
8551200600498x
Davis F D (1989) Perceived usefulness perceived ease of use and user acceptance of information technology MIS
Quarterly 13(3) 319ndash340 httpsdoiorg102307249008
Drazin R amp Van de Ven A H (1985) Alternative forms of fit in contingency theory Administrative Science Quarterly
30(4) 514-539 httpsdoiorg1023072392695
Drent M amp Meelissen M (2008) Which factors obstruct or stimulate teacher educators to use ICT innovatively
Computers amp Education 51 187ndash199 httpsdoiorg101016jcompedu200705001
Eze S C Chinedu-Eze V C amp Bello A O (2018) The utilisation of e-learning facilities in the educational delivery
system of Nigeria A study of M-University International Journal of Educational Technology in Higher Education
15 (34) 1-20 httpsdoiorg101186s41239-018-0116-z
Ferreira A Teixeira A L amp Dantas A R (2015) Non-technological innovation activities mediate the impacts of the
intra- and extra-organisational contexts on technological innovation outputs Enterprise and Work Innovation
Studies 11 9-43
Gerasimova V G Melamud M R Tutaeva D R Romanova Y D amp Zhenova N A (2018) The adoption of e-learning
technology at the Faculty of Distance Learning of Plekhanov Russian University of Economics Journal of Social
Studies Education Research 9(2) 172-188
Glazier R A Hamann K Pollock P H amp B Wilson B M (2019) Age gender and student success Mixing face-to-face
and online courses in political science Journal of Political Science Education 16(2) 142-157 httpsdoiorg1010801551216920181515636
Greene J C Caracelli V J amp Graham W F (1989) Toward a conceptual framework for mixed method evaluation
designs Educational Evaluation and Policy Analysis 11(3) 255-274 httpsdoiorg1023071163620
Gwamba G Renken J Nampijja J Mayende G amp Muyinda P B (2018) Contextualisation of e-learning systems in
higher education institutions In M Auer amp T Tsiatsos (Eds) Interactive mobile communication technologies and
learning Proceedings of the 11th IMCL conference (pp 44-55) Springer
Hardaker G amp Singh G (2011) The adoption and diffusion of eLearning in UK universities A comparative case study
using Giddenss theory of structuration Campus-Wide Information Systems 28(4) 221ndash233
httpsdoiorg10110810650741111162707
Kim H J Hong A J amp Song H (2019) The roles of academic engagement and digital readiness in studentsrsquo
achievements in university e-learning environments International Journal of Educational Technology in Higher
Education 16(21) 1-18 httpsdoiorg101186s41239-019-0152-3
Kimiloglu H Ozturan M amp Kutlu B (2017) Perceptions about and attitude toward the usage of e-learning in corporate
training Computers in Human Behavior 72 339-349 httpsdoiorg101016jchb201702062
Kisanga D amp Ireson G (2015) Barriers and strategies on adoption of e-learning in Tanzanian higher learning institutions
Lessons for adopters International Journal of Education and Development using Information and Communication
Technology (IJEDICT) 11(2) 126-137
Lee Y-K amp Pituch K (2002 December 10ndash13) Moderators in the adoption of e-learning An investigation of the role of
gender [Article] The Second International Conference on Electronic Business Taipei Taiwan
Lippman P C (2010) Can the physical environment have an impact on the learning environment CELE Exchange
httpsdoiorg1017875km4g21wpwr1-en
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 198
Maina M K amp Nzuki D M (2015) Adoption determinants of e-learning management system in institutions of higher
learning in Kenya A case of selected universities in Nairobi metropolitan International Journal of Business and
Social Science 6(2) 233ndash248
Martin M (1991) The culture of the telephone In PD Hopkins (Ed) Sexmachine Readings in culture gender and
technology (pp 50-74) Indiana University Press
Moakofhi M Leteane O Phiri T Pholele T amp Sebalatlheng P (2017) Challenges of introducing e-learning at
Botswana University of Agriculture and Natural Resources Lecturersrsquo perspective International Journal of
Education and Development using ICT 13( 2) 4-20
Nabushawo H M Muyinda P B Isabwe G M N Prinz A amp Mayende G (2018) Improving online interaction among
blended distance learners at Makerere University In M E Auer D Guralnick amp I Simonics (Eds) Advances in
Intelligent Systems and Computing (pp 63-69) Springer httpsdoiorg101007978-3-319-73210-7_8
Odewumi M O Yusuf M O amp Oputa G O (2018) UTAUT model Intention to use social media for learning interactive
effect of postgraduate gender in South-West Nigeria International Journal of Education and Development using
Information and Communication Technology (IJEDICT) 14(3) 239-251
Okai-Ugbaje S Ardzejewska K amp Imran A (2020) Readiness roles and responsibilities of stakeholders for sustainable
mobile learning adoption in higher education Education Sciences 10(3) 49-69
httpsdoiorg103390educsci10030049
Ozkan S amp Koseler R (2009) Multi-dimensional studentsrsquo evaluation of e-learning systems in the higher education
context An empirical investigation Computers amp Education 53(4) 1285ndash1296
httpsdoiorg101016jcompedu200906011
Parlakkılıccedil A (2014) Change management in transition to e-learning system Qualitative and Quantitative Methods in
Libraries 3(3) 637ndash651
Pereira A Martins P Morgado L amp Fonseca B (2018) Technological proposal using virtual worlds to support
entrepreneurship education for primary school children In M E Auer D Guralnick amp I Simonics (Eds)
Advances in Intelligent Systems and Computing (pp 124-132) Springer
Ramiacuterez-Correa P E Arenas-Gaitaacuten J amp Rondaacuten-Cataluntildea F J (2015) Gender and acceptance of e-learning A multi-
group analysis based on a structural equation model among college students in Chile and Spain PLOS ONE
10(10) 1-17 httpsdoiorg101371journalpone0140460
Rhema A amp Miliszewska I (2014) Analysis of student attitudes towards e-learning The case of engineering students in
Libya Issues in Informing Science and Information Technology 11 169-190 httpsdoiorg10289451987
Rogers E M (2003) Diffusion of innovations (5th ed) Free Press
Salinas J (2004) Cambios metodoloacutegicos con las TIC Estrategias didaacutecticas y entornos virtuales de ensentildeanza-aprendizaje
Bordoacuten 56(3-4) 469-481
Selim H M (2007) Critical success factors for e-learning acceptance Confirmatory factor models Computers amp
Education 49(2) 396ndash413 httpsdoi101016jcompedu200509004
Shah M amp Cheng M (2019) Exploring factors impacting student engagement in open access courses Open learning The
Journal of Open Distance and E-Learning 34(2) 187-202 httpsdoiorg1010800268051320181508337
Singh G ODonoghue J amp Worton H (2005) A study into the effects of elearning on higher education Journal of
University Teaching and Learning Practice 2(1) 13-24
Tchamyou V S (2017) The role of knowledge economy in African business Journal of the Knowledge Economy 8(4)
1189ndash1228 httpsdoiorg101007s13132-016-0417-1
The M M amp Usagawa T (2018) A comparative study of studentsrsquo readiness on e-learning education between Indonesia
and Myanmar American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS) 40(1)
113-124
Venkatraman N (1989) The concept of fit in strategy research Toward verbal and statistical correspondence Academy of
Management Review 9(3) 513-525 httpsdoiorg102307258177
Zuvic-Butorac M Nebic Z amp Nemcanin D (2011) Establishing an institutional framework for an e-learning
implementation Experiences from the University of Rijeka Croatia Journal of Information Technology Education
Innovations in Practice 10 43-56 httpsdoiorg10289451364
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Recommended Citation
-
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Cover Page Footnote
-
- tmp1624440487pdfGS9c9
-
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 191
Variable Brief Description of Variables M a Min Max SD
ACC3 Web-based learning 375 1 5 1388
ACC4 Video conferencing 359 1 5 1376
ACC5 University TSL environments eg Black-Board 361 1 5 1536
Organizational Factors
GUELP1 Goal of university TSL policy 297 1 5 1408
ATIEXICT1 Availability of time to experiment with ICT 322 1 5 1366
AFS1 Availability of financial support 273 1 5 1544
COMAN1 Commitment of management 304 1 5 1362
a A score of 350 indicates that the person has and there was ldquoeg intention to use TSL encouragement
on use of TSL facilities and ldquohindrance to the progress of TSL ISsrdquo on the five-point Likert scale of
1(Very little or no intention to use TSL encouragement on use of TSL facilities and hindrance to the
progress of TSL ISs ) and 5(Very much intention to use TSL greatest encouragement on use of TSL
facilities and very much hindrance to the progress of TSL ISs)
Students had lsquomuchrsquo intention to use TSL facilities For instance they had lsquomuchrsquo intention to use
computers (ITU1) The students had lsquomuchrsquo innovative use of TSL (for instance they were able to make
presentations in text audio and video INU2) They also indicated very much acceptance of TSL For
instance they had very much acceptance of computers (ACC1)
See Table 3 for most frequent characteristics of each individual in the whole student population (ie N
=184)
Table 3
Individual Factors (N = 184)
Individual Factors Rate of Occurrence Most Frequent
Individual Factors
AGE Most frequent age of students 25 Years
GEN Most frequent gender of students Male
LEDUC Most frequent year of study of students Year 2
Cluster Analyses
The researchers used the k-means clustering algorithm with the help of Statistica Software version 133
to generate six clusters The data were standardized Whereas several simulations were carried out (ie1
2 3 4 5 and 6) only the sixth simulation showed acceptable results All 6 simulations yielded p values
less than 005 (see Table 4) Table 4 indicates the measurement of the organizational factors and
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 192
adoption of TSL in universities in Uganda across the six student clusters Table 5 shows the
measurement of the individual factors across the said clusters
Table 4
Cluster Analysis and Analysis of Variance for Students
Cluster
Variable 1
(n = 37)
2
(n = 38)
3
(n = 19)
4
(n = 42)
5
(n = 24)
6
(n = 24)
ANOVA
F p
Adoption of TSL
Intention to Use TSL
ITU1 011 024 002 032 048 -161 244 00
ITU2 -007 -074 033 069 -014 -005 1109 00
ITU3 -101 037 035 058 039 -072 2502 00
ITU4 -084 031 031 059 031 -079 1893 00
ITU5 -056 022 -006 059 029 -078 1159 00
Innovative Use of TSL
INU1 -025 051 -024 065 -013 -122 2075 00
INU2 014 029 -142 049 052 -092 2671 00
INU3 -051 044 -128 061 049 -045 2449 00
Acceptance of TSL
ACC1 023 023 007 039 034 -179 3439 00
ACC2 -021 -085 050 092 018 -052 2579 00
ACC3 -087 041 007 064 033 -081 2219 00
ACC4 -100 027 029 067 057 -086 3169 00
ACC5 -065 001 -013 064 066 -069 1529 00
Organizational Factors
GUELP1 004 032 -024 078 -099 -075 2078 00
ATIEXICT1 019 -051 -069 089 -009 -040 1636 00
AFS1 012 -051 -044 105 -053 -036 2228 00
COMAN1 001 -017 -057 074 -018 -039 835 00
Note Positive values are indicated in bold while negative ones are not in bold
Table 5
Individual Factors per Cluster
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
AGE Most frequent
age of
students
26
Years
25
Years
25
Years
25
Years
26
Years
24
Years
356 00
GEN Most frequent
gender of
students
Male Equal
number
of male
and
female
Female Male Male Male 426 00
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 193
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
LEDUC Most frequent
year of
study of
students
Year 2 Year 2 Year 1 Year 2 Year 4 Year 1 409 00
Qualitative Analysis
Thematic analysis was used in analyzing qualitative data We used Braun and Clarke (2006)rsquos six
thematic analysis steps of familiarization generating initial codes searching reviewing defining and
naming themes and producing a report Studentsrsquo data comprised student interview data items from
which initial extracts were made Familiarization was carried out by reading and re-reading the said data
items Generating initial codes was achieved through capturing features of interest from the student data
set Searching was achieved through grouping student data relevant to potential themes Defining and
naming was achieved by categorizing the themes Finally a report about the student data was produced
The researchers used the most significant interview data that could support the quantitative results
presented in this paper in the discussion of findings section Thus the discussion of findings is
integrative
DISCUSSION OF FINDINGS
In this section qualitative findings have been integrated with the quantitative ones The letter lsquoSrsquo
denotes student Cluster 1 students were ranked third as far as the adoption of TSL is concerned because
of the quite weak alignment between the configurational factors For instance the students had no
intention to use web-based technology This was confirmed by student S5 who revealed that she did not
understand web-based learning These students could not interact with their colleagues using TSL
facilities Students in this cluster never embraced video conferencing technology because it is limited as
reflected in the main themes by the students S1 S3 and S5 However these students had the intention to
use computer technology This is consistent with student S1 who commented that ldquoI have the intention
to use computers for academic purposesrdquo They also had innovative use of TSL shown through their
ability to incorporate text audio and visual technology Furthermore these students accepted computer
technology This is supported by students S1 S2 and S6 who revealed that they use computers because
of the current education trend which demands them to be computer literate for academic purposes and
they are easy to work with
Further analysis of this cluster indicates that the organizational factors encourage these students to use
TSL facilities (see Table 4) Qualitative results from students S1 S4 and S3 respectively had the
following implications on the organizational factors
bull the goal of the TSL learning policy encourages the use of TSL facilities at a minimal level
bull students practise with ICT and also believe that the university indirectly supports them financially by
providing limited wireless fidelity
bull the university management is supportive by designing sessions on how to use computers
A typical student in this cluster was 26 years old male by gender and in his second year of study (see
Table 5) While these students have similar characteristics with those of Cluster 6 they have tried to
adopt TSL facilities compared Cluster 6 students because of their experience with such facilities
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 194
Cluster 2 students ranked second as far as adoption of TSL is concerned For example students in this
cluster revealed lsquomuchrsquo intention to use TSL For instance student S1 confirmed that ldquoWeb-based
learning offers more informationrdquo Students in this cluster were lsquovery muchrsquo capable of expounding on
what lecturers had provided to them in class using the Internet This was through ldquosurfingrdquo the Internet
using the Google search engine as revealed by student S1 Students in this cluster had lsquomuchrsquo
acceptance of TSL facilities such as web-based facilities This is because web-based learning can be
used for research work and expounding on what is taught in class by lecturers as revealed by student S1
This is confirmed by a recent study by Chopra et al (2019) that indicates that students are satisfied by
web-based technology
In relation to the organizational factors students in Cluster 2 agreed that the goal of university TSL
policy encourages their use of TSL facilities The qualitative results suggest that e-discussions can
compel students to use TSL facilities as revealed by Student S3 On average students in this cluster
were aged 25 years the number of male students was equivalent to that of female ones and they were in
their second year of study (see Table 5) These students could be better adopters than those of Cluster 1
because they seemed to have an equal gender distribution Such distribution may account for an unequal
educational technology use among Cluster 1 and 2 students who enjoyed a similar learning experience
(see Tables 4 and 5) Students of this cluster seemed to be better adopters than those of Clusters 1 3 5
and 6 because of their ability to make use of the TSL policy to their advantage (see Tables 4 and 5)
Cluster 3 students were low adopters of TSL because of low alignment between the configurational
factors thus ranked fifth as far as adoption of TSL is concerned These students lacked innovative use of
TSL facilities implying that these students cannot use such facilities to improve their learning
capabilities The same students however registered lsquovery muchrsquo acceptance of CD-ROMs (see Table 4)
This could be because this medium is a dependable way of accessing content by students (Kisanga amp
Ireson 2015)
Students in Cluster 3 perceived that the organizational factors never contributed to their use of TSL
facilities in any way (see Table 4) For example students had no time to experiment with ICT This
could be because students never practise with ICT due to the fact that the course is ldquohecticrdquo and the IT
laboratories are usually closed over the weekend as revealed by student S1 The average age gender
and level of education of a student in this cluster is 25 years female and first-year respectively (see
Table 5) These could be lower adopters of TSL than members of Clusters 2 and 5 because of their
gender Female respondents are disadvantaged when it comes to the use of information technology
(Odewumi 2018) Another plausible reason for the low adoption levels in Cluster 3 compared to those
in Clusters 2 and 1 could be the lack of innovative use of TSL (see Table 4)
Cluster 4 students were the greatest adopters of TSL among the six clusters This is because they had the
lsquogreatestrsquo alignment between the configurational factors These students are eager to use ICT innovative
and embraced TSL They are eager to use CD-ROM technology because such technology is cheap and
stores information as confirmed by students S1 and S6 They can innovatively expound on what
lectures have provided to them in class using the Internet with the help of search engines (such as
Google) as indicated by student S1 They have embraced video conference technology Students S1 S3
and S5 confirmed that they were able to imitate the limited video conferencing learning using the
WhatsApp facility
Students in Cluster 4 perceived that the organizational factors encouraged their use of TSL facilities
High scores were registered on the goal of the university TSL policy time to experiment with ICT
financial support and commitment of university management For instance during the interview process
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 195
student S3 revealed that ldquoa discussion policy for example may improve adoption of [TSL] because
once e-discussions are made they can compel one to use the [TSL] facilitiesrdquo The result from the
interview process on time to experiment with TSL conflicts with the cluster one whereby the majority
of the students never found time to practise with TSL facilities Shah and Cheng (2019) however
indicate that time influences the adoption of TSL facilities Quantitative findings in this cluster on
financial support could be related to those of student S3 who indicated that there was indirect financial
support by their university through the provision of wireless technology On the issue of management
commitment findings are in line with those of student S4 who felt that university management was
committed because they designed computer literacy sessions for them A typical student in this cluster
was 25 years old male by gender and in year 2 of study (see Table 5) This cluster (n = 42) had the
majority of the student respondents among the six clusters
The alignment of the configurational factors in Cluster 5 seemed to be lsquoweakerrsquo than that of Cluster 1
thus this cluster was ranked fourth Whereas the students in this cluster indicated lsquovery muchrsquo adoption
of TSL in some instances the configurational variables registered low scores For instance they had
very much acceptance of TSL environments yet they seemed not to be familiar with the TSL policy
The result on acceptance of TSL environments is parallel to that of Bond et al (2018) who indicated that
such environments are commonly used by students in higher education institutions in Germany The
result on the TSL policy was confirmed by student S4 who revealed that the TSL policy is not
effectively implemented in the university A normal student in this cluster was 26 years old male by
gender and in year 4 of the study (see Table 5) These students could be better adopters of TSL than
those of Clusters 3 and 6 because of their long-time experience with TSL as reflected in their year of
study compared to the said clusters (see Tables 4 and 5) It is not surprising this cluster had the best
distributions of ICTs among students
Similar to Cluster 5 Cluster 6 had 24 respondents (see Table 4) However students in this cluster are
coincidentally ranked as non-adopters of TSL among the six clusters (see Tables 4 and 5) This is
because there is no alignment between the configurational factors resulting in no adoption of TSL
These students were not willing to use IT could not modify their learning capabilities using IT and had
not realised the value of IT tools All 24 respondents in this cluster lsquoconcurredrsquo that the organization
never encouraged their use of TSL facilities This could imply that students were not involved at all
during the adoption of TSL Shah and Cheng (2019) reveal that students perceive that juggling work and
study caring for children financial difficulty and academic writing among other factors affect their
ability to adopt TSL On average students in this cluster were 26 years old male by gender and in year
1 of their study Being in their first year of study could imply that they had little experience with TSL
CONCLUSION
Identification of predictors of successful adoption of TSL among students was achieved using the
Gestalts approach Students perceived that organizational and individual factors predict successful
adoption of TSL Cluster 4 is the most coherent and as such adopted TSL most This is because the
organizational and individual factors were most aligned For example when students in this cluster are
financially supported and are in their second year of study they are eager to use to be innovative with
and embrace TSL And because of their eagerness innovativeness and ability to embrace TSL they have
accumulated more experience than others Cluster 6 students are non-adopters because they are more
inexperienced with TSL than the rest of the students
There seems to be a gap in the use of the non-linear techniques (eg clustering technique) in studies on
studentsrsquo perceptions Most studies for instance Chopra et al (2019) Gerasimova et al (2018) and Shah
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 196
and Cheng (2019) who have measured student perceptions have used linear techniques Thus this study
has closed this gap This study is a benchmark for universities in developing economies to integrate TSL
at university level For instance it should be noted that in order to achieve successful adoption of TSL
among students in universities management must be involved Nabushawo et al (2018) suggest that the
commitment of management can be achieved by collaborating with and training the users of TSL ISs
Since the world is challenged by Corona Virus Disease (COVID) this study can be used as model to
avail learning materials to students without spreading this disease
It should be noted that the rate of adoption of TSL among students is still low yet they have advanced in
age This contradicts Pereira et al (2018) who indicated that adoption of TSL usually takes place at an
early age It is therefore recommended that students should be supported to adopt TSL during their
earlier career years so that universities in Uganda can benefit from this innovation This can be done by
introducing TSL at primary level Universities need to strengthen their management capabilities such as
increasing the time studentsrsquo have to experiment with ICTs Further research is required to develop
strategies that can be adopted to enhance adoption of TSL among students at earlier ages Although this
study was carried out at a particular point in time it can also be carried out longitudinally There are
many indicators of the organization individual (student) and adoption of TSL besides those presented in
the conceptual framework Further research can be carried out on those Besides organization and
individual factors there is need to know the role of other factors in the adoption of TSL among students
While students from only two public universities were considered for this study students from other
universities can be considered as well
ACKNOWLEDGMENTS
The researchers want to thank the Almighty God for the gift of knowledge wisdom and understanding
in the writing of this paper The researchers also thank the Organization for Women in Science for the
Developing World (OWSD) and the Swedish International Development Agency (SIDA) for their
financial support in carrying out the study
REFERENCES
Acosta M L Sisley A Ross J Brailsford I Bhargava A Jacobs R amp Anstice N (2018) Student acceptance of e-
learning methods in the laboratory class in optometry PLOS ONE 13(12) 1-15
httpsdoiorg101371journalpone0209004
Adewole-Odeshi E (2014) Attitude of students towards e-learning in South-West Nigerian universities An application of
technology acceptance model Library Philosophy and Practice Article 1035
Angolia M G amp Pagliari L R (2016) Factors for successful evolution and sustainability of quality distance education
Online Journal of Distance Learning Administration 19(3)
Ayele B A amp Birhanie W K (2018) Acceptance and use of e-learning systems The case of teachers in technology
institutes of Ethiopian universities Applied Informatics 5(1) 1-11 httpsdoiorg101186s40535-018-0048-7
Back D A von Malotky J Sostmann K Peters H Hube R amp Hoff E (2019) Experiences with using e-learning tools
in orthopedics in an uncontrolled field study application Orthopaedics amp Traumatology Surgery amp Research
105(2) 389-393 httpsdoiorg101016jotsr201901002
Bhardwaj A amp Goundar S (2018) Students perspective of elearning and the future of education with MOOCs
International Journal of Computer Engineering 7(5) 248-260
Bhattacherjee A (2012) Social science research Principles methods and practices Textbooks Collection
httpscholarcommonsusfeduoa_textbooks3
Bond M Mariacuten V I Dolch C Bedenlier S amp Zawacki-Ritcher O (2018) Digital transformation in German higher
education Student and teacher perceptions and usage of digital media International Journal of Educational
Technology in Higher Education 15(48) httpsdoiorg101186s41239-018-0130-1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 197
Braun V amp Clarke V (2006) Using thematic analysis in psychology Qualitative Research in Psychology 33 77-101
Chopra G Madan P Jaisingh P amp Bhaskar P (2019) Effectiveness of e-learning portal from studentsrsquo perspective A
structural equation model (SEM) approach Interactive Technology and Smart Education 16(2) 94-116
httpsdoiorg101108ITSE-05-2018-0027
Creswell J W (2014) Research Design Qualitative quantitative and mixed methods approaches (4th ed) Sage
Publications
Damanpour F amp Schneider M (2006) Phases of the adoption of innovation in organisations Effects of environment
organisation and top managers British Journal of Management 17 215ndash236 httpsdoiorg101111j1467-
8551200600498x
Davis F D (1989) Perceived usefulness perceived ease of use and user acceptance of information technology MIS
Quarterly 13(3) 319ndash340 httpsdoiorg102307249008
Drazin R amp Van de Ven A H (1985) Alternative forms of fit in contingency theory Administrative Science Quarterly
30(4) 514-539 httpsdoiorg1023072392695
Drent M amp Meelissen M (2008) Which factors obstruct or stimulate teacher educators to use ICT innovatively
Computers amp Education 51 187ndash199 httpsdoiorg101016jcompedu200705001
Eze S C Chinedu-Eze V C amp Bello A O (2018) The utilisation of e-learning facilities in the educational delivery
system of Nigeria A study of M-University International Journal of Educational Technology in Higher Education
15 (34) 1-20 httpsdoiorg101186s41239-018-0116-z
Ferreira A Teixeira A L amp Dantas A R (2015) Non-technological innovation activities mediate the impacts of the
intra- and extra-organisational contexts on technological innovation outputs Enterprise and Work Innovation
Studies 11 9-43
Gerasimova V G Melamud M R Tutaeva D R Romanova Y D amp Zhenova N A (2018) The adoption of e-learning
technology at the Faculty of Distance Learning of Plekhanov Russian University of Economics Journal of Social
Studies Education Research 9(2) 172-188
Glazier R A Hamann K Pollock P H amp B Wilson B M (2019) Age gender and student success Mixing face-to-face
and online courses in political science Journal of Political Science Education 16(2) 142-157 httpsdoiorg1010801551216920181515636
Greene J C Caracelli V J amp Graham W F (1989) Toward a conceptual framework for mixed method evaluation
designs Educational Evaluation and Policy Analysis 11(3) 255-274 httpsdoiorg1023071163620
Gwamba G Renken J Nampijja J Mayende G amp Muyinda P B (2018) Contextualisation of e-learning systems in
higher education institutions In M Auer amp T Tsiatsos (Eds) Interactive mobile communication technologies and
learning Proceedings of the 11th IMCL conference (pp 44-55) Springer
Hardaker G amp Singh G (2011) The adoption and diffusion of eLearning in UK universities A comparative case study
using Giddenss theory of structuration Campus-Wide Information Systems 28(4) 221ndash233
httpsdoiorg10110810650741111162707
Kim H J Hong A J amp Song H (2019) The roles of academic engagement and digital readiness in studentsrsquo
achievements in university e-learning environments International Journal of Educational Technology in Higher
Education 16(21) 1-18 httpsdoiorg101186s41239-019-0152-3
Kimiloglu H Ozturan M amp Kutlu B (2017) Perceptions about and attitude toward the usage of e-learning in corporate
training Computers in Human Behavior 72 339-349 httpsdoiorg101016jchb201702062
Kisanga D amp Ireson G (2015) Barriers and strategies on adoption of e-learning in Tanzanian higher learning institutions
Lessons for adopters International Journal of Education and Development using Information and Communication
Technology (IJEDICT) 11(2) 126-137
Lee Y-K amp Pituch K (2002 December 10ndash13) Moderators in the adoption of e-learning An investigation of the role of
gender [Article] The Second International Conference on Electronic Business Taipei Taiwan
Lippman P C (2010) Can the physical environment have an impact on the learning environment CELE Exchange
httpsdoiorg1017875km4g21wpwr1-en
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 198
Maina M K amp Nzuki D M (2015) Adoption determinants of e-learning management system in institutions of higher
learning in Kenya A case of selected universities in Nairobi metropolitan International Journal of Business and
Social Science 6(2) 233ndash248
Martin M (1991) The culture of the telephone In PD Hopkins (Ed) Sexmachine Readings in culture gender and
technology (pp 50-74) Indiana University Press
Moakofhi M Leteane O Phiri T Pholele T amp Sebalatlheng P (2017) Challenges of introducing e-learning at
Botswana University of Agriculture and Natural Resources Lecturersrsquo perspective International Journal of
Education and Development using ICT 13( 2) 4-20
Nabushawo H M Muyinda P B Isabwe G M N Prinz A amp Mayende G (2018) Improving online interaction among
blended distance learners at Makerere University In M E Auer D Guralnick amp I Simonics (Eds) Advances in
Intelligent Systems and Computing (pp 63-69) Springer httpsdoiorg101007978-3-319-73210-7_8
Odewumi M O Yusuf M O amp Oputa G O (2018) UTAUT model Intention to use social media for learning interactive
effect of postgraduate gender in South-West Nigeria International Journal of Education and Development using
Information and Communication Technology (IJEDICT) 14(3) 239-251
Okai-Ugbaje S Ardzejewska K amp Imran A (2020) Readiness roles and responsibilities of stakeholders for sustainable
mobile learning adoption in higher education Education Sciences 10(3) 49-69
httpsdoiorg103390educsci10030049
Ozkan S amp Koseler R (2009) Multi-dimensional studentsrsquo evaluation of e-learning systems in the higher education
context An empirical investigation Computers amp Education 53(4) 1285ndash1296
httpsdoiorg101016jcompedu200906011
Parlakkılıccedil A (2014) Change management in transition to e-learning system Qualitative and Quantitative Methods in
Libraries 3(3) 637ndash651
Pereira A Martins P Morgado L amp Fonseca B (2018) Technological proposal using virtual worlds to support
entrepreneurship education for primary school children In M E Auer D Guralnick amp I Simonics (Eds)
Advances in Intelligent Systems and Computing (pp 124-132) Springer
Ramiacuterez-Correa P E Arenas-Gaitaacuten J amp Rondaacuten-Cataluntildea F J (2015) Gender and acceptance of e-learning A multi-
group analysis based on a structural equation model among college students in Chile and Spain PLOS ONE
10(10) 1-17 httpsdoiorg101371journalpone0140460
Rhema A amp Miliszewska I (2014) Analysis of student attitudes towards e-learning The case of engineering students in
Libya Issues in Informing Science and Information Technology 11 169-190 httpsdoiorg10289451987
Rogers E M (2003) Diffusion of innovations (5th ed) Free Press
Salinas J (2004) Cambios metodoloacutegicos con las TIC Estrategias didaacutecticas y entornos virtuales de ensentildeanza-aprendizaje
Bordoacuten 56(3-4) 469-481
Selim H M (2007) Critical success factors for e-learning acceptance Confirmatory factor models Computers amp
Education 49(2) 396ndash413 httpsdoi101016jcompedu200509004
Shah M amp Cheng M (2019) Exploring factors impacting student engagement in open access courses Open learning The
Journal of Open Distance and E-Learning 34(2) 187-202 httpsdoiorg1010800268051320181508337
Singh G ODonoghue J amp Worton H (2005) A study into the effects of elearning on higher education Journal of
University Teaching and Learning Practice 2(1) 13-24
Tchamyou V S (2017) The role of knowledge economy in African business Journal of the Knowledge Economy 8(4)
1189ndash1228 httpsdoiorg101007s13132-016-0417-1
The M M amp Usagawa T (2018) A comparative study of studentsrsquo readiness on e-learning education between Indonesia
and Myanmar American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS) 40(1)
113-124
Venkatraman N (1989) The concept of fit in strategy research Toward verbal and statistical correspondence Academy of
Management Review 9(3) 513-525 httpsdoiorg102307258177
Zuvic-Butorac M Nebic Z amp Nemcanin D (2011) Establishing an institutional framework for an e-learning
implementation Experiences from the University of Rijeka Croatia Journal of Information Technology Education
Innovations in Practice 10 43-56 httpsdoiorg10289451364
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Recommended Citation
-
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Cover Page Footnote
-
- tmp1624440487pdfGS9c9
-
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 192
adoption of TSL in universities in Uganda across the six student clusters Table 5 shows the
measurement of the individual factors across the said clusters
Table 4
Cluster Analysis and Analysis of Variance for Students
Cluster
Variable 1
(n = 37)
2
(n = 38)
3
(n = 19)
4
(n = 42)
5
(n = 24)
6
(n = 24)
ANOVA
F p
Adoption of TSL
Intention to Use TSL
ITU1 011 024 002 032 048 -161 244 00
ITU2 -007 -074 033 069 -014 -005 1109 00
ITU3 -101 037 035 058 039 -072 2502 00
ITU4 -084 031 031 059 031 -079 1893 00
ITU5 -056 022 -006 059 029 -078 1159 00
Innovative Use of TSL
INU1 -025 051 -024 065 -013 -122 2075 00
INU2 014 029 -142 049 052 -092 2671 00
INU3 -051 044 -128 061 049 -045 2449 00
Acceptance of TSL
ACC1 023 023 007 039 034 -179 3439 00
ACC2 -021 -085 050 092 018 -052 2579 00
ACC3 -087 041 007 064 033 -081 2219 00
ACC4 -100 027 029 067 057 -086 3169 00
ACC5 -065 001 -013 064 066 -069 1529 00
Organizational Factors
GUELP1 004 032 -024 078 -099 -075 2078 00
ATIEXICT1 019 -051 -069 089 -009 -040 1636 00
AFS1 012 -051 -044 105 -053 -036 2228 00
COMAN1 001 -017 -057 074 -018 -039 835 00
Note Positive values are indicated in bold while negative ones are not in bold
Table 5
Individual Factors per Cluster
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
AGE Most frequent
age of
students
26
Years
25
Years
25
Years
25
Years
26
Years
24
Years
356 00
GEN Most frequent
gender of
students
Male Equal
number
of male
and
female
Female Male Male Male 426 00
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 193
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
LEDUC Most frequent
year of
study of
students
Year 2 Year 2 Year 1 Year 2 Year 4 Year 1 409 00
Qualitative Analysis
Thematic analysis was used in analyzing qualitative data We used Braun and Clarke (2006)rsquos six
thematic analysis steps of familiarization generating initial codes searching reviewing defining and
naming themes and producing a report Studentsrsquo data comprised student interview data items from
which initial extracts were made Familiarization was carried out by reading and re-reading the said data
items Generating initial codes was achieved through capturing features of interest from the student data
set Searching was achieved through grouping student data relevant to potential themes Defining and
naming was achieved by categorizing the themes Finally a report about the student data was produced
The researchers used the most significant interview data that could support the quantitative results
presented in this paper in the discussion of findings section Thus the discussion of findings is
integrative
DISCUSSION OF FINDINGS
In this section qualitative findings have been integrated with the quantitative ones The letter lsquoSrsquo
denotes student Cluster 1 students were ranked third as far as the adoption of TSL is concerned because
of the quite weak alignment between the configurational factors For instance the students had no
intention to use web-based technology This was confirmed by student S5 who revealed that she did not
understand web-based learning These students could not interact with their colleagues using TSL
facilities Students in this cluster never embraced video conferencing technology because it is limited as
reflected in the main themes by the students S1 S3 and S5 However these students had the intention to
use computer technology This is consistent with student S1 who commented that ldquoI have the intention
to use computers for academic purposesrdquo They also had innovative use of TSL shown through their
ability to incorporate text audio and visual technology Furthermore these students accepted computer
technology This is supported by students S1 S2 and S6 who revealed that they use computers because
of the current education trend which demands them to be computer literate for academic purposes and
they are easy to work with
Further analysis of this cluster indicates that the organizational factors encourage these students to use
TSL facilities (see Table 4) Qualitative results from students S1 S4 and S3 respectively had the
following implications on the organizational factors
bull the goal of the TSL learning policy encourages the use of TSL facilities at a minimal level
bull students practise with ICT and also believe that the university indirectly supports them financially by
providing limited wireless fidelity
bull the university management is supportive by designing sessions on how to use computers
A typical student in this cluster was 26 years old male by gender and in his second year of study (see
Table 5) While these students have similar characteristics with those of Cluster 6 they have tried to
adopt TSL facilities compared Cluster 6 students because of their experience with such facilities
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 194
Cluster 2 students ranked second as far as adoption of TSL is concerned For example students in this
cluster revealed lsquomuchrsquo intention to use TSL For instance student S1 confirmed that ldquoWeb-based
learning offers more informationrdquo Students in this cluster were lsquovery muchrsquo capable of expounding on
what lecturers had provided to them in class using the Internet This was through ldquosurfingrdquo the Internet
using the Google search engine as revealed by student S1 Students in this cluster had lsquomuchrsquo
acceptance of TSL facilities such as web-based facilities This is because web-based learning can be
used for research work and expounding on what is taught in class by lecturers as revealed by student S1
This is confirmed by a recent study by Chopra et al (2019) that indicates that students are satisfied by
web-based technology
In relation to the organizational factors students in Cluster 2 agreed that the goal of university TSL
policy encourages their use of TSL facilities The qualitative results suggest that e-discussions can
compel students to use TSL facilities as revealed by Student S3 On average students in this cluster
were aged 25 years the number of male students was equivalent to that of female ones and they were in
their second year of study (see Table 5) These students could be better adopters than those of Cluster 1
because they seemed to have an equal gender distribution Such distribution may account for an unequal
educational technology use among Cluster 1 and 2 students who enjoyed a similar learning experience
(see Tables 4 and 5) Students of this cluster seemed to be better adopters than those of Clusters 1 3 5
and 6 because of their ability to make use of the TSL policy to their advantage (see Tables 4 and 5)
Cluster 3 students were low adopters of TSL because of low alignment between the configurational
factors thus ranked fifth as far as adoption of TSL is concerned These students lacked innovative use of
TSL facilities implying that these students cannot use such facilities to improve their learning
capabilities The same students however registered lsquovery muchrsquo acceptance of CD-ROMs (see Table 4)
This could be because this medium is a dependable way of accessing content by students (Kisanga amp
Ireson 2015)
Students in Cluster 3 perceived that the organizational factors never contributed to their use of TSL
facilities in any way (see Table 4) For example students had no time to experiment with ICT This
could be because students never practise with ICT due to the fact that the course is ldquohecticrdquo and the IT
laboratories are usually closed over the weekend as revealed by student S1 The average age gender
and level of education of a student in this cluster is 25 years female and first-year respectively (see
Table 5) These could be lower adopters of TSL than members of Clusters 2 and 5 because of their
gender Female respondents are disadvantaged when it comes to the use of information technology
(Odewumi 2018) Another plausible reason for the low adoption levels in Cluster 3 compared to those
in Clusters 2 and 1 could be the lack of innovative use of TSL (see Table 4)
Cluster 4 students were the greatest adopters of TSL among the six clusters This is because they had the
lsquogreatestrsquo alignment between the configurational factors These students are eager to use ICT innovative
and embraced TSL They are eager to use CD-ROM technology because such technology is cheap and
stores information as confirmed by students S1 and S6 They can innovatively expound on what
lectures have provided to them in class using the Internet with the help of search engines (such as
Google) as indicated by student S1 They have embraced video conference technology Students S1 S3
and S5 confirmed that they were able to imitate the limited video conferencing learning using the
WhatsApp facility
Students in Cluster 4 perceived that the organizational factors encouraged their use of TSL facilities
High scores were registered on the goal of the university TSL policy time to experiment with ICT
financial support and commitment of university management For instance during the interview process
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 195
student S3 revealed that ldquoa discussion policy for example may improve adoption of [TSL] because
once e-discussions are made they can compel one to use the [TSL] facilitiesrdquo The result from the
interview process on time to experiment with TSL conflicts with the cluster one whereby the majority
of the students never found time to practise with TSL facilities Shah and Cheng (2019) however
indicate that time influences the adoption of TSL facilities Quantitative findings in this cluster on
financial support could be related to those of student S3 who indicated that there was indirect financial
support by their university through the provision of wireless technology On the issue of management
commitment findings are in line with those of student S4 who felt that university management was
committed because they designed computer literacy sessions for them A typical student in this cluster
was 25 years old male by gender and in year 2 of study (see Table 5) This cluster (n = 42) had the
majority of the student respondents among the six clusters
The alignment of the configurational factors in Cluster 5 seemed to be lsquoweakerrsquo than that of Cluster 1
thus this cluster was ranked fourth Whereas the students in this cluster indicated lsquovery muchrsquo adoption
of TSL in some instances the configurational variables registered low scores For instance they had
very much acceptance of TSL environments yet they seemed not to be familiar with the TSL policy
The result on acceptance of TSL environments is parallel to that of Bond et al (2018) who indicated that
such environments are commonly used by students in higher education institutions in Germany The
result on the TSL policy was confirmed by student S4 who revealed that the TSL policy is not
effectively implemented in the university A normal student in this cluster was 26 years old male by
gender and in year 4 of the study (see Table 5) These students could be better adopters of TSL than
those of Clusters 3 and 6 because of their long-time experience with TSL as reflected in their year of
study compared to the said clusters (see Tables 4 and 5) It is not surprising this cluster had the best
distributions of ICTs among students
Similar to Cluster 5 Cluster 6 had 24 respondents (see Table 4) However students in this cluster are
coincidentally ranked as non-adopters of TSL among the six clusters (see Tables 4 and 5) This is
because there is no alignment between the configurational factors resulting in no adoption of TSL
These students were not willing to use IT could not modify their learning capabilities using IT and had
not realised the value of IT tools All 24 respondents in this cluster lsquoconcurredrsquo that the organization
never encouraged their use of TSL facilities This could imply that students were not involved at all
during the adoption of TSL Shah and Cheng (2019) reveal that students perceive that juggling work and
study caring for children financial difficulty and academic writing among other factors affect their
ability to adopt TSL On average students in this cluster were 26 years old male by gender and in year
1 of their study Being in their first year of study could imply that they had little experience with TSL
CONCLUSION
Identification of predictors of successful adoption of TSL among students was achieved using the
Gestalts approach Students perceived that organizational and individual factors predict successful
adoption of TSL Cluster 4 is the most coherent and as such adopted TSL most This is because the
organizational and individual factors were most aligned For example when students in this cluster are
financially supported and are in their second year of study they are eager to use to be innovative with
and embrace TSL And because of their eagerness innovativeness and ability to embrace TSL they have
accumulated more experience than others Cluster 6 students are non-adopters because they are more
inexperienced with TSL than the rest of the students
There seems to be a gap in the use of the non-linear techniques (eg clustering technique) in studies on
studentsrsquo perceptions Most studies for instance Chopra et al (2019) Gerasimova et al (2018) and Shah
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 196
and Cheng (2019) who have measured student perceptions have used linear techniques Thus this study
has closed this gap This study is a benchmark for universities in developing economies to integrate TSL
at university level For instance it should be noted that in order to achieve successful adoption of TSL
among students in universities management must be involved Nabushawo et al (2018) suggest that the
commitment of management can be achieved by collaborating with and training the users of TSL ISs
Since the world is challenged by Corona Virus Disease (COVID) this study can be used as model to
avail learning materials to students without spreading this disease
It should be noted that the rate of adoption of TSL among students is still low yet they have advanced in
age This contradicts Pereira et al (2018) who indicated that adoption of TSL usually takes place at an
early age It is therefore recommended that students should be supported to adopt TSL during their
earlier career years so that universities in Uganda can benefit from this innovation This can be done by
introducing TSL at primary level Universities need to strengthen their management capabilities such as
increasing the time studentsrsquo have to experiment with ICTs Further research is required to develop
strategies that can be adopted to enhance adoption of TSL among students at earlier ages Although this
study was carried out at a particular point in time it can also be carried out longitudinally There are
many indicators of the organization individual (student) and adoption of TSL besides those presented in
the conceptual framework Further research can be carried out on those Besides organization and
individual factors there is need to know the role of other factors in the adoption of TSL among students
While students from only two public universities were considered for this study students from other
universities can be considered as well
ACKNOWLEDGMENTS
The researchers want to thank the Almighty God for the gift of knowledge wisdom and understanding
in the writing of this paper The researchers also thank the Organization for Women in Science for the
Developing World (OWSD) and the Swedish International Development Agency (SIDA) for their
financial support in carrying out the study
REFERENCES
Acosta M L Sisley A Ross J Brailsford I Bhargava A Jacobs R amp Anstice N (2018) Student acceptance of e-
learning methods in the laboratory class in optometry PLOS ONE 13(12) 1-15
httpsdoiorg101371journalpone0209004
Adewole-Odeshi E (2014) Attitude of students towards e-learning in South-West Nigerian universities An application of
technology acceptance model Library Philosophy and Practice Article 1035
Angolia M G amp Pagliari L R (2016) Factors for successful evolution and sustainability of quality distance education
Online Journal of Distance Learning Administration 19(3)
Ayele B A amp Birhanie W K (2018) Acceptance and use of e-learning systems The case of teachers in technology
institutes of Ethiopian universities Applied Informatics 5(1) 1-11 httpsdoiorg101186s40535-018-0048-7
Back D A von Malotky J Sostmann K Peters H Hube R amp Hoff E (2019) Experiences with using e-learning tools
in orthopedics in an uncontrolled field study application Orthopaedics amp Traumatology Surgery amp Research
105(2) 389-393 httpsdoiorg101016jotsr201901002
Bhardwaj A amp Goundar S (2018) Students perspective of elearning and the future of education with MOOCs
International Journal of Computer Engineering 7(5) 248-260
Bhattacherjee A (2012) Social science research Principles methods and practices Textbooks Collection
httpscholarcommonsusfeduoa_textbooks3
Bond M Mariacuten V I Dolch C Bedenlier S amp Zawacki-Ritcher O (2018) Digital transformation in German higher
education Student and teacher perceptions and usage of digital media International Journal of Educational
Technology in Higher Education 15(48) httpsdoiorg101186s41239-018-0130-1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 197
Braun V amp Clarke V (2006) Using thematic analysis in psychology Qualitative Research in Psychology 33 77-101
Chopra G Madan P Jaisingh P amp Bhaskar P (2019) Effectiveness of e-learning portal from studentsrsquo perspective A
structural equation model (SEM) approach Interactive Technology and Smart Education 16(2) 94-116
httpsdoiorg101108ITSE-05-2018-0027
Creswell J W (2014) Research Design Qualitative quantitative and mixed methods approaches (4th ed) Sage
Publications
Damanpour F amp Schneider M (2006) Phases of the adoption of innovation in organisations Effects of environment
organisation and top managers British Journal of Management 17 215ndash236 httpsdoiorg101111j1467-
8551200600498x
Davis F D (1989) Perceived usefulness perceived ease of use and user acceptance of information technology MIS
Quarterly 13(3) 319ndash340 httpsdoiorg102307249008
Drazin R amp Van de Ven A H (1985) Alternative forms of fit in contingency theory Administrative Science Quarterly
30(4) 514-539 httpsdoiorg1023072392695
Drent M amp Meelissen M (2008) Which factors obstruct or stimulate teacher educators to use ICT innovatively
Computers amp Education 51 187ndash199 httpsdoiorg101016jcompedu200705001
Eze S C Chinedu-Eze V C amp Bello A O (2018) The utilisation of e-learning facilities in the educational delivery
system of Nigeria A study of M-University International Journal of Educational Technology in Higher Education
15 (34) 1-20 httpsdoiorg101186s41239-018-0116-z
Ferreira A Teixeira A L amp Dantas A R (2015) Non-technological innovation activities mediate the impacts of the
intra- and extra-organisational contexts on technological innovation outputs Enterprise and Work Innovation
Studies 11 9-43
Gerasimova V G Melamud M R Tutaeva D R Romanova Y D amp Zhenova N A (2018) The adoption of e-learning
technology at the Faculty of Distance Learning of Plekhanov Russian University of Economics Journal of Social
Studies Education Research 9(2) 172-188
Glazier R A Hamann K Pollock P H amp B Wilson B M (2019) Age gender and student success Mixing face-to-face
and online courses in political science Journal of Political Science Education 16(2) 142-157 httpsdoiorg1010801551216920181515636
Greene J C Caracelli V J amp Graham W F (1989) Toward a conceptual framework for mixed method evaluation
designs Educational Evaluation and Policy Analysis 11(3) 255-274 httpsdoiorg1023071163620
Gwamba G Renken J Nampijja J Mayende G amp Muyinda P B (2018) Contextualisation of e-learning systems in
higher education institutions In M Auer amp T Tsiatsos (Eds) Interactive mobile communication technologies and
learning Proceedings of the 11th IMCL conference (pp 44-55) Springer
Hardaker G amp Singh G (2011) The adoption and diffusion of eLearning in UK universities A comparative case study
using Giddenss theory of structuration Campus-Wide Information Systems 28(4) 221ndash233
httpsdoiorg10110810650741111162707
Kim H J Hong A J amp Song H (2019) The roles of academic engagement and digital readiness in studentsrsquo
achievements in university e-learning environments International Journal of Educational Technology in Higher
Education 16(21) 1-18 httpsdoiorg101186s41239-019-0152-3
Kimiloglu H Ozturan M amp Kutlu B (2017) Perceptions about and attitude toward the usage of e-learning in corporate
training Computers in Human Behavior 72 339-349 httpsdoiorg101016jchb201702062
Kisanga D amp Ireson G (2015) Barriers and strategies on adoption of e-learning in Tanzanian higher learning institutions
Lessons for adopters International Journal of Education and Development using Information and Communication
Technology (IJEDICT) 11(2) 126-137
Lee Y-K amp Pituch K (2002 December 10ndash13) Moderators in the adoption of e-learning An investigation of the role of
gender [Article] The Second International Conference on Electronic Business Taipei Taiwan
Lippman P C (2010) Can the physical environment have an impact on the learning environment CELE Exchange
httpsdoiorg1017875km4g21wpwr1-en
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 198
Maina M K amp Nzuki D M (2015) Adoption determinants of e-learning management system in institutions of higher
learning in Kenya A case of selected universities in Nairobi metropolitan International Journal of Business and
Social Science 6(2) 233ndash248
Martin M (1991) The culture of the telephone In PD Hopkins (Ed) Sexmachine Readings in culture gender and
technology (pp 50-74) Indiana University Press
Moakofhi M Leteane O Phiri T Pholele T amp Sebalatlheng P (2017) Challenges of introducing e-learning at
Botswana University of Agriculture and Natural Resources Lecturersrsquo perspective International Journal of
Education and Development using ICT 13( 2) 4-20
Nabushawo H M Muyinda P B Isabwe G M N Prinz A amp Mayende G (2018) Improving online interaction among
blended distance learners at Makerere University In M E Auer D Guralnick amp I Simonics (Eds) Advances in
Intelligent Systems and Computing (pp 63-69) Springer httpsdoiorg101007978-3-319-73210-7_8
Odewumi M O Yusuf M O amp Oputa G O (2018) UTAUT model Intention to use social media for learning interactive
effect of postgraduate gender in South-West Nigeria International Journal of Education and Development using
Information and Communication Technology (IJEDICT) 14(3) 239-251
Okai-Ugbaje S Ardzejewska K amp Imran A (2020) Readiness roles and responsibilities of stakeholders for sustainable
mobile learning adoption in higher education Education Sciences 10(3) 49-69
httpsdoiorg103390educsci10030049
Ozkan S amp Koseler R (2009) Multi-dimensional studentsrsquo evaluation of e-learning systems in the higher education
context An empirical investigation Computers amp Education 53(4) 1285ndash1296
httpsdoiorg101016jcompedu200906011
Parlakkılıccedil A (2014) Change management in transition to e-learning system Qualitative and Quantitative Methods in
Libraries 3(3) 637ndash651
Pereira A Martins P Morgado L amp Fonseca B (2018) Technological proposal using virtual worlds to support
entrepreneurship education for primary school children In M E Auer D Guralnick amp I Simonics (Eds)
Advances in Intelligent Systems and Computing (pp 124-132) Springer
Ramiacuterez-Correa P E Arenas-Gaitaacuten J amp Rondaacuten-Cataluntildea F J (2015) Gender and acceptance of e-learning A multi-
group analysis based on a structural equation model among college students in Chile and Spain PLOS ONE
10(10) 1-17 httpsdoiorg101371journalpone0140460
Rhema A amp Miliszewska I (2014) Analysis of student attitudes towards e-learning The case of engineering students in
Libya Issues in Informing Science and Information Technology 11 169-190 httpsdoiorg10289451987
Rogers E M (2003) Diffusion of innovations (5th ed) Free Press
Salinas J (2004) Cambios metodoloacutegicos con las TIC Estrategias didaacutecticas y entornos virtuales de ensentildeanza-aprendizaje
Bordoacuten 56(3-4) 469-481
Selim H M (2007) Critical success factors for e-learning acceptance Confirmatory factor models Computers amp
Education 49(2) 396ndash413 httpsdoi101016jcompedu200509004
Shah M amp Cheng M (2019) Exploring factors impacting student engagement in open access courses Open learning The
Journal of Open Distance and E-Learning 34(2) 187-202 httpsdoiorg1010800268051320181508337
Singh G ODonoghue J amp Worton H (2005) A study into the effects of elearning on higher education Journal of
University Teaching and Learning Practice 2(1) 13-24
Tchamyou V S (2017) The role of knowledge economy in African business Journal of the Knowledge Economy 8(4)
1189ndash1228 httpsdoiorg101007s13132-016-0417-1
The M M amp Usagawa T (2018) A comparative study of studentsrsquo readiness on e-learning education between Indonesia
and Myanmar American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS) 40(1)
113-124
Venkatraman N (1989) The concept of fit in strategy research Toward verbal and statistical correspondence Academy of
Management Review 9(3) 513-525 httpsdoiorg102307258177
Zuvic-Butorac M Nebic Z amp Nemcanin D (2011) Establishing an institutional framework for an e-learning
implementation Experiences from the University of Rijeka Croatia Journal of Information Technology Education
Innovations in Practice 10 43-56 httpsdoiorg10289451364
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Recommended Citation
-
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Cover Page Footnote
-
- tmp1624440487pdfGS9c9
-
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 193
Individual
Factors
Rate of
Occurrence
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
ANOVA
F p
LEDUC Most frequent
year of
study of
students
Year 2 Year 2 Year 1 Year 2 Year 4 Year 1 409 00
Qualitative Analysis
Thematic analysis was used in analyzing qualitative data We used Braun and Clarke (2006)rsquos six
thematic analysis steps of familiarization generating initial codes searching reviewing defining and
naming themes and producing a report Studentsrsquo data comprised student interview data items from
which initial extracts were made Familiarization was carried out by reading and re-reading the said data
items Generating initial codes was achieved through capturing features of interest from the student data
set Searching was achieved through grouping student data relevant to potential themes Defining and
naming was achieved by categorizing the themes Finally a report about the student data was produced
The researchers used the most significant interview data that could support the quantitative results
presented in this paper in the discussion of findings section Thus the discussion of findings is
integrative
DISCUSSION OF FINDINGS
In this section qualitative findings have been integrated with the quantitative ones The letter lsquoSrsquo
denotes student Cluster 1 students were ranked third as far as the adoption of TSL is concerned because
of the quite weak alignment between the configurational factors For instance the students had no
intention to use web-based technology This was confirmed by student S5 who revealed that she did not
understand web-based learning These students could not interact with their colleagues using TSL
facilities Students in this cluster never embraced video conferencing technology because it is limited as
reflected in the main themes by the students S1 S3 and S5 However these students had the intention to
use computer technology This is consistent with student S1 who commented that ldquoI have the intention
to use computers for academic purposesrdquo They also had innovative use of TSL shown through their
ability to incorporate text audio and visual technology Furthermore these students accepted computer
technology This is supported by students S1 S2 and S6 who revealed that they use computers because
of the current education trend which demands them to be computer literate for academic purposes and
they are easy to work with
Further analysis of this cluster indicates that the organizational factors encourage these students to use
TSL facilities (see Table 4) Qualitative results from students S1 S4 and S3 respectively had the
following implications on the organizational factors
bull the goal of the TSL learning policy encourages the use of TSL facilities at a minimal level
bull students practise with ICT and also believe that the university indirectly supports them financially by
providing limited wireless fidelity
bull the university management is supportive by designing sessions on how to use computers
A typical student in this cluster was 26 years old male by gender and in his second year of study (see
Table 5) While these students have similar characteristics with those of Cluster 6 they have tried to
adopt TSL facilities compared Cluster 6 students because of their experience with such facilities
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 194
Cluster 2 students ranked second as far as adoption of TSL is concerned For example students in this
cluster revealed lsquomuchrsquo intention to use TSL For instance student S1 confirmed that ldquoWeb-based
learning offers more informationrdquo Students in this cluster were lsquovery muchrsquo capable of expounding on
what lecturers had provided to them in class using the Internet This was through ldquosurfingrdquo the Internet
using the Google search engine as revealed by student S1 Students in this cluster had lsquomuchrsquo
acceptance of TSL facilities such as web-based facilities This is because web-based learning can be
used for research work and expounding on what is taught in class by lecturers as revealed by student S1
This is confirmed by a recent study by Chopra et al (2019) that indicates that students are satisfied by
web-based technology
In relation to the organizational factors students in Cluster 2 agreed that the goal of university TSL
policy encourages their use of TSL facilities The qualitative results suggest that e-discussions can
compel students to use TSL facilities as revealed by Student S3 On average students in this cluster
were aged 25 years the number of male students was equivalent to that of female ones and they were in
their second year of study (see Table 5) These students could be better adopters than those of Cluster 1
because they seemed to have an equal gender distribution Such distribution may account for an unequal
educational technology use among Cluster 1 and 2 students who enjoyed a similar learning experience
(see Tables 4 and 5) Students of this cluster seemed to be better adopters than those of Clusters 1 3 5
and 6 because of their ability to make use of the TSL policy to their advantage (see Tables 4 and 5)
Cluster 3 students were low adopters of TSL because of low alignment between the configurational
factors thus ranked fifth as far as adoption of TSL is concerned These students lacked innovative use of
TSL facilities implying that these students cannot use such facilities to improve their learning
capabilities The same students however registered lsquovery muchrsquo acceptance of CD-ROMs (see Table 4)
This could be because this medium is a dependable way of accessing content by students (Kisanga amp
Ireson 2015)
Students in Cluster 3 perceived that the organizational factors never contributed to their use of TSL
facilities in any way (see Table 4) For example students had no time to experiment with ICT This
could be because students never practise with ICT due to the fact that the course is ldquohecticrdquo and the IT
laboratories are usually closed over the weekend as revealed by student S1 The average age gender
and level of education of a student in this cluster is 25 years female and first-year respectively (see
Table 5) These could be lower adopters of TSL than members of Clusters 2 and 5 because of their
gender Female respondents are disadvantaged when it comes to the use of information technology
(Odewumi 2018) Another plausible reason for the low adoption levels in Cluster 3 compared to those
in Clusters 2 and 1 could be the lack of innovative use of TSL (see Table 4)
Cluster 4 students were the greatest adopters of TSL among the six clusters This is because they had the
lsquogreatestrsquo alignment between the configurational factors These students are eager to use ICT innovative
and embraced TSL They are eager to use CD-ROM technology because such technology is cheap and
stores information as confirmed by students S1 and S6 They can innovatively expound on what
lectures have provided to them in class using the Internet with the help of search engines (such as
Google) as indicated by student S1 They have embraced video conference technology Students S1 S3
and S5 confirmed that they were able to imitate the limited video conferencing learning using the
WhatsApp facility
Students in Cluster 4 perceived that the organizational factors encouraged their use of TSL facilities
High scores were registered on the goal of the university TSL policy time to experiment with ICT
financial support and commitment of university management For instance during the interview process
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 195
student S3 revealed that ldquoa discussion policy for example may improve adoption of [TSL] because
once e-discussions are made they can compel one to use the [TSL] facilitiesrdquo The result from the
interview process on time to experiment with TSL conflicts with the cluster one whereby the majority
of the students never found time to practise with TSL facilities Shah and Cheng (2019) however
indicate that time influences the adoption of TSL facilities Quantitative findings in this cluster on
financial support could be related to those of student S3 who indicated that there was indirect financial
support by their university through the provision of wireless technology On the issue of management
commitment findings are in line with those of student S4 who felt that university management was
committed because they designed computer literacy sessions for them A typical student in this cluster
was 25 years old male by gender and in year 2 of study (see Table 5) This cluster (n = 42) had the
majority of the student respondents among the six clusters
The alignment of the configurational factors in Cluster 5 seemed to be lsquoweakerrsquo than that of Cluster 1
thus this cluster was ranked fourth Whereas the students in this cluster indicated lsquovery muchrsquo adoption
of TSL in some instances the configurational variables registered low scores For instance they had
very much acceptance of TSL environments yet they seemed not to be familiar with the TSL policy
The result on acceptance of TSL environments is parallel to that of Bond et al (2018) who indicated that
such environments are commonly used by students in higher education institutions in Germany The
result on the TSL policy was confirmed by student S4 who revealed that the TSL policy is not
effectively implemented in the university A normal student in this cluster was 26 years old male by
gender and in year 4 of the study (see Table 5) These students could be better adopters of TSL than
those of Clusters 3 and 6 because of their long-time experience with TSL as reflected in their year of
study compared to the said clusters (see Tables 4 and 5) It is not surprising this cluster had the best
distributions of ICTs among students
Similar to Cluster 5 Cluster 6 had 24 respondents (see Table 4) However students in this cluster are
coincidentally ranked as non-adopters of TSL among the six clusters (see Tables 4 and 5) This is
because there is no alignment between the configurational factors resulting in no adoption of TSL
These students were not willing to use IT could not modify their learning capabilities using IT and had
not realised the value of IT tools All 24 respondents in this cluster lsquoconcurredrsquo that the organization
never encouraged their use of TSL facilities This could imply that students were not involved at all
during the adoption of TSL Shah and Cheng (2019) reveal that students perceive that juggling work and
study caring for children financial difficulty and academic writing among other factors affect their
ability to adopt TSL On average students in this cluster were 26 years old male by gender and in year
1 of their study Being in their first year of study could imply that they had little experience with TSL
CONCLUSION
Identification of predictors of successful adoption of TSL among students was achieved using the
Gestalts approach Students perceived that organizational and individual factors predict successful
adoption of TSL Cluster 4 is the most coherent and as such adopted TSL most This is because the
organizational and individual factors were most aligned For example when students in this cluster are
financially supported and are in their second year of study they are eager to use to be innovative with
and embrace TSL And because of their eagerness innovativeness and ability to embrace TSL they have
accumulated more experience than others Cluster 6 students are non-adopters because they are more
inexperienced with TSL than the rest of the students
There seems to be a gap in the use of the non-linear techniques (eg clustering technique) in studies on
studentsrsquo perceptions Most studies for instance Chopra et al (2019) Gerasimova et al (2018) and Shah
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 196
and Cheng (2019) who have measured student perceptions have used linear techniques Thus this study
has closed this gap This study is a benchmark for universities in developing economies to integrate TSL
at university level For instance it should be noted that in order to achieve successful adoption of TSL
among students in universities management must be involved Nabushawo et al (2018) suggest that the
commitment of management can be achieved by collaborating with and training the users of TSL ISs
Since the world is challenged by Corona Virus Disease (COVID) this study can be used as model to
avail learning materials to students without spreading this disease
It should be noted that the rate of adoption of TSL among students is still low yet they have advanced in
age This contradicts Pereira et al (2018) who indicated that adoption of TSL usually takes place at an
early age It is therefore recommended that students should be supported to adopt TSL during their
earlier career years so that universities in Uganda can benefit from this innovation This can be done by
introducing TSL at primary level Universities need to strengthen their management capabilities such as
increasing the time studentsrsquo have to experiment with ICTs Further research is required to develop
strategies that can be adopted to enhance adoption of TSL among students at earlier ages Although this
study was carried out at a particular point in time it can also be carried out longitudinally There are
many indicators of the organization individual (student) and adoption of TSL besides those presented in
the conceptual framework Further research can be carried out on those Besides organization and
individual factors there is need to know the role of other factors in the adoption of TSL among students
While students from only two public universities were considered for this study students from other
universities can be considered as well
ACKNOWLEDGMENTS
The researchers want to thank the Almighty God for the gift of knowledge wisdom and understanding
in the writing of this paper The researchers also thank the Organization for Women in Science for the
Developing World (OWSD) and the Swedish International Development Agency (SIDA) for their
financial support in carrying out the study
REFERENCES
Acosta M L Sisley A Ross J Brailsford I Bhargava A Jacobs R amp Anstice N (2018) Student acceptance of e-
learning methods in the laboratory class in optometry PLOS ONE 13(12) 1-15
httpsdoiorg101371journalpone0209004
Adewole-Odeshi E (2014) Attitude of students towards e-learning in South-West Nigerian universities An application of
technology acceptance model Library Philosophy and Practice Article 1035
Angolia M G amp Pagliari L R (2016) Factors for successful evolution and sustainability of quality distance education
Online Journal of Distance Learning Administration 19(3)
Ayele B A amp Birhanie W K (2018) Acceptance and use of e-learning systems The case of teachers in technology
institutes of Ethiopian universities Applied Informatics 5(1) 1-11 httpsdoiorg101186s40535-018-0048-7
Back D A von Malotky J Sostmann K Peters H Hube R amp Hoff E (2019) Experiences with using e-learning tools
in orthopedics in an uncontrolled field study application Orthopaedics amp Traumatology Surgery amp Research
105(2) 389-393 httpsdoiorg101016jotsr201901002
Bhardwaj A amp Goundar S (2018) Students perspective of elearning and the future of education with MOOCs
International Journal of Computer Engineering 7(5) 248-260
Bhattacherjee A (2012) Social science research Principles methods and practices Textbooks Collection
httpscholarcommonsusfeduoa_textbooks3
Bond M Mariacuten V I Dolch C Bedenlier S amp Zawacki-Ritcher O (2018) Digital transformation in German higher
education Student and teacher perceptions and usage of digital media International Journal of Educational
Technology in Higher Education 15(48) httpsdoiorg101186s41239-018-0130-1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 197
Braun V amp Clarke V (2006) Using thematic analysis in psychology Qualitative Research in Psychology 33 77-101
Chopra G Madan P Jaisingh P amp Bhaskar P (2019) Effectiveness of e-learning portal from studentsrsquo perspective A
structural equation model (SEM) approach Interactive Technology and Smart Education 16(2) 94-116
httpsdoiorg101108ITSE-05-2018-0027
Creswell J W (2014) Research Design Qualitative quantitative and mixed methods approaches (4th ed) Sage
Publications
Damanpour F amp Schneider M (2006) Phases of the adoption of innovation in organisations Effects of environment
organisation and top managers British Journal of Management 17 215ndash236 httpsdoiorg101111j1467-
8551200600498x
Davis F D (1989) Perceived usefulness perceived ease of use and user acceptance of information technology MIS
Quarterly 13(3) 319ndash340 httpsdoiorg102307249008
Drazin R amp Van de Ven A H (1985) Alternative forms of fit in contingency theory Administrative Science Quarterly
30(4) 514-539 httpsdoiorg1023072392695
Drent M amp Meelissen M (2008) Which factors obstruct or stimulate teacher educators to use ICT innovatively
Computers amp Education 51 187ndash199 httpsdoiorg101016jcompedu200705001
Eze S C Chinedu-Eze V C amp Bello A O (2018) The utilisation of e-learning facilities in the educational delivery
system of Nigeria A study of M-University International Journal of Educational Technology in Higher Education
15 (34) 1-20 httpsdoiorg101186s41239-018-0116-z
Ferreira A Teixeira A L amp Dantas A R (2015) Non-technological innovation activities mediate the impacts of the
intra- and extra-organisational contexts on technological innovation outputs Enterprise and Work Innovation
Studies 11 9-43
Gerasimova V G Melamud M R Tutaeva D R Romanova Y D amp Zhenova N A (2018) The adoption of e-learning
technology at the Faculty of Distance Learning of Plekhanov Russian University of Economics Journal of Social
Studies Education Research 9(2) 172-188
Glazier R A Hamann K Pollock P H amp B Wilson B M (2019) Age gender and student success Mixing face-to-face
and online courses in political science Journal of Political Science Education 16(2) 142-157 httpsdoiorg1010801551216920181515636
Greene J C Caracelli V J amp Graham W F (1989) Toward a conceptual framework for mixed method evaluation
designs Educational Evaluation and Policy Analysis 11(3) 255-274 httpsdoiorg1023071163620
Gwamba G Renken J Nampijja J Mayende G amp Muyinda P B (2018) Contextualisation of e-learning systems in
higher education institutions In M Auer amp T Tsiatsos (Eds) Interactive mobile communication technologies and
learning Proceedings of the 11th IMCL conference (pp 44-55) Springer
Hardaker G amp Singh G (2011) The adoption and diffusion of eLearning in UK universities A comparative case study
using Giddenss theory of structuration Campus-Wide Information Systems 28(4) 221ndash233
httpsdoiorg10110810650741111162707
Kim H J Hong A J amp Song H (2019) The roles of academic engagement and digital readiness in studentsrsquo
achievements in university e-learning environments International Journal of Educational Technology in Higher
Education 16(21) 1-18 httpsdoiorg101186s41239-019-0152-3
Kimiloglu H Ozturan M amp Kutlu B (2017) Perceptions about and attitude toward the usage of e-learning in corporate
training Computers in Human Behavior 72 339-349 httpsdoiorg101016jchb201702062
Kisanga D amp Ireson G (2015) Barriers and strategies on adoption of e-learning in Tanzanian higher learning institutions
Lessons for adopters International Journal of Education and Development using Information and Communication
Technology (IJEDICT) 11(2) 126-137
Lee Y-K amp Pituch K (2002 December 10ndash13) Moderators in the adoption of e-learning An investigation of the role of
gender [Article] The Second International Conference on Electronic Business Taipei Taiwan
Lippman P C (2010) Can the physical environment have an impact on the learning environment CELE Exchange
httpsdoiorg1017875km4g21wpwr1-en
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 198
Maina M K amp Nzuki D M (2015) Adoption determinants of e-learning management system in institutions of higher
learning in Kenya A case of selected universities in Nairobi metropolitan International Journal of Business and
Social Science 6(2) 233ndash248
Martin M (1991) The culture of the telephone In PD Hopkins (Ed) Sexmachine Readings in culture gender and
technology (pp 50-74) Indiana University Press
Moakofhi M Leteane O Phiri T Pholele T amp Sebalatlheng P (2017) Challenges of introducing e-learning at
Botswana University of Agriculture and Natural Resources Lecturersrsquo perspective International Journal of
Education and Development using ICT 13( 2) 4-20
Nabushawo H M Muyinda P B Isabwe G M N Prinz A amp Mayende G (2018) Improving online interaction among
blended distance learners at Makerere University In M E Auer D Guralnick amp I Simonics (Eds) Advances in
Intelligent Systems and Computing (pp 63-69) Springer httpsdoiorg101007978-3-319-73210-7_8
Odewumi M O Yusuf M O amp Oputa G O (2018) UTAUT model Intention to use social media for learning interactive
effect of postgraduate gender in South-West Nigeria International Journal of Education and Development using
Information and Communication Technology (IJEDICT) 14(3) 239-251
Okai-Ugbaje S Ardzejewska K amp Imran A (2020) Readiness roles and responsibilities of stakeholders for sustainable
mobile learning adoption in higher education Education Sciences 10(3) 49-69
httpsdoiorg103390educsci10030049
Ozkan S amp Koseler R (2009) Multi-dimensional studentsrsquo evaluation of e-learning systems in the higher education
context An empirical investigation Computers amp Education 53(4) 1285ndash1296
httpsdoiorg101016jcompedu200906011
Parlakkılıccedil A (2014) Change management in transition to e-learning system Qualitative and Quantitative Methods in
Libraries 3(3) 637ndash651
Pereira A Martins P Morgado L amp Fonseca B (2018) Technological proposal using virtual worlds to support
entrepreneurship education for primary school children In M E Auer D Guralnick amp I Simonics (Eds)
Advances in Intelligent Systems and Computing (pp 124-132) Springer
Ramiacuterez-Correa P E Arenas-Gaitaacuten J amp Rondaacuten-Cataluntildea F J (2015) Gender and acceptance of e-learning A multi-
group analysis based on a structural equation model among college students in Chile and Spain PLOS ONE
10(10) 1-17 httpsdoiorg101371journalpone0140460
Rhema A amp Miliszewska I (2014) Analysis of student attitudes towards e-learning The case of engineering students in
Libya Issues in Informing Science and Information Technology 11 169-190 httpsdoiorg10289451987
Rogers E M (2003) Diffusion of innovations (5th ed) Free Press
Salinas J (2004) Cambios metodoloacutegicos con las TIC Estrategias didaacutecticas y entornos virtuales de ensentildeanza-aprendizaje
Bordoacuten 56(3-4) 469-481
Selim H M (2007) Critical success factors for e-learning acceptance Confirmatory factor models Computers amp
Education 49(2) 396ndash413 httpsdoi101016jcompedu200509004
Shah M amp Cheng M (2019) Exploring factors impacting student engagement in open access courses Open learning The
Journal of Open Distance and E-Learning 34(2) 187-202 httpsdoiorg1010800268051320181508337
Singh G ODonoghue J amp Worton H (2005) A study into the effects of elearning on higher education Journal of
University Teaching and Learning Practice 2(1) 13-24
Tchamyou V S (2017) The role of knowledge economy in African business Journal of the Knowledge Economy 8(4)
1189ndash1228 httpsdoiorg101007s13132-016-0417-1
The M M amp Usagawa T (2018) A comparative study of studentsrsquo readiness on e-learning education between Indonesia
and Myanmar American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS) 40(1)
113-124
Venkatraman N (1989) The concept of fit in strategy research Toward verbal and statistical correspondence Academy of
Management Review 9(3) 513-525 httpsdoiorg102307258177
Zuvic-Butorac M Nebic Z amp Nemcanin D (2011) Establishing an institutional framework for an e-learning
implementation Experiences from the University of Rijeka Croatia Journal of Information Technology Education
Innovations in Practice 10 43-56 httpsdoiorg10289451364
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Recommended Citation
-
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Cover Page Footnote
-
- tmp1624440487pdfGS9c9
-
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 194
Cluster 2 students ranked second as far as adoption of TSL is concerned For example students in this
cluster revealed lsquomuchrsquo intention to use TSL For instance student S1 confirmed that ldquoWeb-based
learning offers more informationrdquo Students in this cluster were lsquovery muchrsquo capable of expounding on
what lecturers had provided to them in class using the Internet This was through ldquosurfingrdquo the Internet
using the Google search engine as revealed by student S1 Students in this cluster had lsquomuchrsquo
acceptance of TSL facilities such as web-based facilities This is because web-based learning can be
used for research work and expounding on what is taught in class by lecturers as revealed by student S1
This is confirmed by a recent study by Chopra et al (2019) that indicates that students are satisfied by
web-based technology
In relation to the organizational factors students in Cluster 2 agreed that the goal of university TSL
policy encourages their use of TSL facilities The qualitative results suggest that e-discussions can
compel students to use TSL facilities as revealed by Student S3 On average students in this cluster
were aged 25 years the number of male students was equivalent to that of female ones and they were in
their second year of study (see Table 5) These students could be better adopters than those of Cluster 1
because they seemed to have an equal gender distribution Such distribution may account for an unequal
educational technology use among Cluster 1 and 2 students who enjoyed a similar learning experience
(see Tables 4 and 5) Students of this cluster seemed to be better adopters than those of Clusters 1 3 5
and 6 because of their ability to make use of the TSL policy to their advantage (see Tables 4 and 5)
Cluster 3 students were low adopters of TSL because of low alignment between the configurational
factors thus ranked fifth as far as adoption of TSL is concerned These students lacked innovative use of
TSL facilities implying that these students cannot use such facilities to improve their learning
capabilities The same students however registered lsquovery muchrsquo acceptance of CD-ROMs (see Table 4)
This could be because this medium is a dependable way of accessing content by students (Kisanga amp
Ireson 2015)
Students in Cluster 3 perceived that the organizational factors never contributed to their use of TSL
facilities in any way (see Table 4) For example students had no time to experiment with ICT This
could be because students never practise with ICT due to the fact that the course is ldquohecticrdquo and the IT
laboratories are usually closed over the weekend as revealed by student S1 The average age gender
and level of education of a student in this cluster is 25 years female and first-year respectively (see
Table 5) These could be lower adopters of TSL than members of Clusters 2 and 5 because of their
gender Female respondents are disadvantaged when it comes to the use of information technology
(Odewumi 2018) Another plausible reason for the low adoption levels in Cluster 3 compared to those
in Clusters 2 and 1 could be the lack of innovative use of TSL (see Table 4)
Cluster 4 students were the greatest adopters of TSL among the six clusters This is because they had the
lsquogreatestrsquo alignment between the configurational factors These students are eager to use ICT innovative
and embraced TSL They are eager to use CD-ROM technology because such technology is cheap and
stores information as confirmed by students S1 and S6 They can innovatively expound on what
lectures have provided to them in class using the Internet with the help of search engines (such as
Google) as indicated by student S1 They have embraced video conference technology Students S1 S3
and S5 confirmed that they were able to imitate the limited video conferencing learning using the
WhatsApp facility
Students in Cluster 4 perceived that the organizational factors encouraged their use of TSL facilities
High scores were registered on the goal of the university TSL policy time to experiment with ICT
financial support and commitment of university management For instance during the interview process
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 195
student S3 revealed that ldquoa discussion policy for example may improve adoption of [TSL] because
once e-discussions are made they can compel one to use the [TSL] facilitiesrdquo The result from the
interview process on time to experiment with TSL conflicts with the cluster one whereby the majority
of the students never found time to practise with TSL facilities Shah and Cheng (2019) however
indicate that time influences the adoption of TSL facilities Quantitative findings in this cluster on
financial support could be related to those of student S3 who indicated that there was indirect financial
support by their university through the provision of wireless technology On the issue of management
commitment findings are in line with those of student S4 who felt that university management was
committed because they designed computer literacy sessions for them A typical student in this cluster
was 25 years old male by gender and in year 2 of study (see Table 5) This cluster (n = 42) had the
majority of the student respondents among the six clusters
The alignment of the configurational factors in Cluster 5 seemed to be lsquoweakerrsquo than that of Cluster 1
thus this cluster was ranked fourth Whereas the students in this cluster indicated lsquovery muchrsquo adoption
of TSL in some instances the configurational variables registered low scores For instance they had
very much acceptance of TSL environments yet they seemed not to be familiar with the TSL policy
The result on acceptance of TSL environments is parallel to that of Bond et al (2018) who indicated that
such environments are commonly used by students in higher education institutions in Germany The
result on the TSL policy was confirmed by student S4 who revealed that the TSL policy is not
effectively implemented in the university A normal student in this cluster was 26 years old male by
gender and in year 4 of the study (see Table 5) These students could be better adopters of TSL than
those of Clusters 3 and 6 because of their long-time experience with TSL as reflected in their year of
study compared to the said clusters (see Tables 4 and 5) It is not surprising this cluster had the best
distributions of ICTs among students
Similar to Cluster 5 Cluster 6 had 24 respondents (see Table 4) However students in this cluster are
coincidentally ranked as non-adopters of TSL among the six clusters (see Tables 4 and 5) This is
because there is no alignment between the configurational factors resulting in no adoption of TSL
These students were not willing to use IT could not modify their learning capabilities using IT and had
not realised the value of IT tools All 24 respondents in this cluster lsquoconcurredrsquo that the organization
never encouraged their use of TSL facilities This could imply that students were not involved at all
during the adoption of TSL Shah and Cheng (2019) reveal that students perceive that juggling work and
study caring for children financial difficulty and academic writing among other factors affect their
ability to adopt TSL On average students in this cluster were 26 years old male by gender and in year
1 of their study Being in their first year of study could imply that they had little experience with TSL
CONCLUSION
Identification of predictors of successful adoption of TSL among students was achieved using the
Gestalts approach Students perceived that organizational and individual factors predict successful
adoption of TSL Cluster 4 is the most coherent and as such adopted TSL most This is because the
organizational and individual factors were most aligned For example when students in this cluster are
financially supported and are in their second year of study they are eager to use to be innovative with
and embrace TSL And because of their eagerness innovativeness and ability to embrace TSL they have
accumulated more experience than others Cluster 6 students are non-adopters because they are more
inexperienced with TSL than the rest of the students
There seems to be a gap in the use of the non-linear techniques (eg clustering technique) in studies on
studentsrsquo perceptions Most studies for instance Chopra et al (2019) Gerasimova et al (2018) and Shah
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 196
and Cheng (2019) who have measured student perceptions have used linear techniques Thus this study
has closed this gap This study is a benchmark for universities in developing economies to integrate TSL
at university level For instance it should be noted that in order to achieve successful adoption of TSL
among students in universities management must be involved Nabushawo et al (2018) suggest that the
commitment of management can be achieved by collaborating with and training the users of TSL ISs
Since the world is challenged by Corona Virus Disease (COVID) this study can be used as model to
avail learning materials to students without spreading this disease
It should be noted that the rate of adoption of TSL among students is still low yet they have advanced in
age This contradicts Pereira et al (2018) who indicated that adoption of TSL usually takes place at an
early age It is therefore recommended that students should be supported to adopt TSL during their
earlier career years so that universities in Uganda can benefit from this innovation This can be done by
introducing TSL at primary level Universities need to strengthen their management capabilities such as
increasing the time studentsrsquo have to experiment with ICTs Further research is required to develop
strategies that can be adopted to enhance adoption of TSL among students at earlier ages Although this
study was carried out at a particular point in time it can also be carried out longitudinally There are
many indicators of the organization individual (student) and adoption of TSL besides those presented in
the conceptual framework Further research can be carried out on those Besides organization and
individual factors there is need to know the role of other factors in the adoption of TSL among students
While students from only two public universities were considered for this study students from other
universities can be considered as well
ACKNOWLEDGMENTS
The researchers want to thank the Almighty God for the gift of knowledge wisdom and understanding
in the writing of this paper The researchers also thank the Organization for Women in Science for the
Developing World (OWSD) and the Swedish International Development Agency (SIDA) for their
financial support in carrying out the study
REFERENCES
Acosta M L Sisley A Ross J Brailsford I Bhargava A Jacobs R amp Anstice N (2018) Student acceptance of e-
learning methods in the laboratory class in optometry PLOS ONE 13(12) 1-15
httpsdoiorg101371journalpone0209004
Adewole-Odeshi E (2014) Attitude of students towards e-learning in South-West Nigerian universities An application of
technology acceptance model Library Philosophy and Practice Article 1035
Angolia M G amp Pagliari L R (2016) Factors for successful evolution and sustainability of quality distance education
Online Journal of Distance Learning Administration 19(3)
Ayele B A amp Birhanie W K (2018) Acceptance and use of e-learning systems The case of teachers in technology
institutes of Ethiopian universities Applied Informatics 5(1) 1-11 httpsdoiorg101186s40535-018-0048-7
Back D A von Malotky J Sostmann K Peters H Hube R amp Hoff E (2019) Experiences with using e-learning tools
in orthopedics in an uncontrolled field study application Orthopaedics amp Traumatology Surgery amp Research
105(2) 389-393 httpsdoiorg101016jotsr201901002
Bhardwaj A amp Goundar S (2018) Students perspective of elearning and the future of education with MOOCs
International Journal of Computer Engineering 7(5) 248-260
Bhattacherjee A (2012) Social science research Principles methods and practices Textbooks Collection
httpscholarcommonsusfeduoa_textbooks3
Bond M Mariacuten V I Dolch C Bedenlier S amp Zawacki-Ritcher O (2018) Digital transformation in German higher
education Student and teacher perceptions and usage of digital media International Journal of Educational
Technology in Higher Education 15(48) httpsdoiorg101186s41239-018-0130-1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 197
Braun V amp Clarke V (2006) Using thematic analysis in psychology Qualitative Research in Psychology 33 77-101
Chopra G Madan P Jaisingh P amp Bhaskar P (2019) Effectiveness of e-learning portal from studentsrsquo perspective A
structural equation model (SEM) approach Interactive Technology and Smart Education 16(2) 94-116
httpsdoiorg101108ITSE-05-2018-0027
Creswell J W (2014) Research Design Qualitative quantitative and mixed methods approaches (4th ed) Sage
Publications
Damanpour F amp Schneider M (2006) Phases of the adoption of innovation in organisations Effects of environment
organisation and top managers British Journal of Management 17 215ndash236 httpsdoiorg101111j1467-
8551200600498x
Davis F D (1989) Perceived usefulness perceived ease of use and user acceptance of information technology MIS
Quarterly 13(3) 319ndash340 httpsdoiorg102307249008
Drazin R amp Van de Ven A H (1985) Alternative forms of fit in contingency theory Administrative Science Quarterly
30(4) 514-539 httpsdoiorg1023072392695
Drent M amp Meelissen M (2008) Which factors obstruct or stimulate teacher educators to use ICT innovatively
Computers amp Education 51 187ndash199 httpsdoiorg101016jcompedu200705001
Eze S C Chinedu-Eze V C amp Bello A O (2018) The utilisation of e-learning facilities in the educational delivery
system of Nigeria A study of M-University International Journal of Educational Technology in Higher Education
15 (34) 1-20 httpsdoiorg101186s41239-018-0116-z
Ferreira A Teixeira A L amp Dantas A R (2015) Non-technological innovation activities mediate the impacts of the
intra- and extra-organisational contexts on technological innovation outputs Enterprise and Work Innovation
Studies 11 9-43
Gerasimova V G Melamud M R Tutaeva D R Romanova Y D amp Zhenova N A (2018) The adoption of e-learning
technology at the Faculty of Distance Learning of Plekhanov Russian University of Economics Journal of Social
Studies Education Research 9(2) 172-188
Glazier R A Hamann K Pollock P H amp B Wilson B M (2019) Age gender and student success Mixing face-to-face
and online courses in political science Journal of Political Science Education 16(2) 142-157 httpsdoiorg1010801551216920181515636
Greene J C Caracelli V J amp Graham W F (1989) Toward a conceptual framework for mixed method evaluation
designs Educational Evaluation and Policy Analysis 11(3) 255-274 httpsdoiorg1023071163620
Gwamba G Renken J Nampijja J Mayende G amp Muyinda P B (2018) Contextualisation of e-learning systems in
higher education institutions In M Auer amp T Tsiatsos (Eds) Interactive mobile communication technologies and
learning Proceedings of the 11th IMCL conference (pp 44-55) Springer
Hardaker G amp Singh G (2011) The adoption and diffusion of eLearning in UK universities A comparative case study
using Giddenss theory of structuration Campus-Wide Information Systems 28(4) 221ndash233
httpsdoiorg10110810650741111162707
Kim H J Hong A J amp Song H (2019) The roles of academic engagement and digital readiness in studentsrsquo
achievements in university e-learning environments International Journal of Educational Technology in Higher
Education 16(21) 1-18 httpsdoiorg101186s41239-019-0152-3
Kimiloglu H Ozturan M amp Kutlu B (2017) Perceptions about and attitude toward the usage of e-learning in corporate
training Computers in Human Behavior 72 339-349 httpsdoiorg101016jchb201702062
Kisanga D amp Ireson G (2015) Barriers and strategies on adoption of e-learning in Tanzanian higher learning institutions
Lessons for adopters International Journal of Education and Development using Information and Communication
Technology (IJEDICT) 11(2) 126-137
Lee Y-K amp Pituch K (2002 December 10ndash13) Moderators in the adoption of e-learning An investigation of the role of
gender [Article] The Second International Conference on Electronic Business Taipei Taiwan
Lippman P C (2010) Can the physical environment have an impact on the learning environment CELE Exchange
httpsdoiorg1017875km4g21wpwr1-en
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 198
Maina M K amp Nzuki D M (2015) Adoption determinants of e-learning management system in institutions of higher
learning in Kenya A case of selected universities in Nairobi metropolitan International Journal of Business and
Social Science 6(2) 233ndash248
Martin M (1991) The culture of the telephone In PD Hopkins (Ed) Sexmachine Readings in culture gender and
technology (pp 50-74) Indiana University Press
Moakofhi M Leteane O Phiri T Pholele T amp Sebalatlheng P (2017) Challenges of introducing e-learning at
Botswana University of Agriculture and Natural Resources Lecturersrsquo perspective International Journal of
Education and Development using ICT 13( 2) 4-20
Nabushawo H M Muyinda P B Isabwe G M N Prinz A amp Mayende G (2018) Improving online interaction among
blended distance learners at Makerere University In M E Auer D Guralnick amp I Simonics (Eds) Advances in
Intelligent Systems and Computing (pp 63-69) Springer httpsdoiorg101007978-3-319-73210-7_8
Odewumi M O Yusuf M O amp Oputa G O (2018) UTAUT model Intention to use social media for learning interactive
effect of postgraduate gender in South-West Nigeria International Journal of Education and Development using
Information and Communication Technology (IJEDICT) 14(3) 239-251
Okai-Ugbaje S Ardzejewska K amp Imran A (2020) Readiness roles and responsibilities of stakeholders for sustainable
mobile learning adoption in higher education Education Sciences 10(3) 49-69
httpsdoiorg103390educsci10030049
Ozkan S amp Koseler R (2009) Multi-dimensional studentsrsquo evaluation of e-learning systems in the higher education
context An empirical investigation Computers amp Education 53(4) 1285ndash1296
httpsdoiorg101016jcompedu200906011
Parlakkılıccedil A (2014) Change management in transition to e-learning system Qualitative and Quantitative Methods in
Libraries 3(3) 637ndash651
Pereira A Martins P Morgado L amp Fonseca B (2018) Technological proposal using virtual worlds to support
entrepreneurship education for primary school children In M E Auer D Guralnick amp I Simonics (Eds)
Advances in Intelligent Systems and Computing (pp 124-132) Springer
Ramiacuterez-Correa P E Arenas-Gaitaacuten J amp Rondaacuten-Cataluntildea F J (2015) Gender and acceptance of e-learning A multi-
group analysis based on a structural equation model among college students in Chile and Spain PLOS ONE
10(10) 1-17 httpsdoiorg101371journalpone0140460
Rhema A amp Miliszewska I (2014) Analysis of student attitudes towards e-learning The case of engineering students in
Libya Issues in Informing Science and Information Technology 11 169-190 httpsdoiorg10289451987
Rogers E M (2003) Diffusion of innovations (5th ed) Free Press
Salinas J (2004) Cambios metodoloacutegicos con las TIC Estrategias didaacutecticas y entornos virtuales de ensentildeanza-aprendizaje
Bordoacuten 56(3-4) 469-481
Selim H M (2007) Critical success factors for e-learning acceptance Confirmatory factor models Computers amp
Education 49(2) 396ndash413 httpsdoi101016jcompedu200509004
Shah M amp Cheng M (2019) Exploring factors impacting student engagement in open access courses Open learning The
Journal of Open Distance and E-Learning 34(2) 187-202 httpsdoiorg1010800268051320181508337
Singh G ODonoghue J amp Worton H (2005) A study into the effects of elearning on higher education Journal of
University Teaching and Learning Practice 2(1) 13-24
Tchamyou V S (2017) The role of knowledge economy in African business Journal of the Knowledge Economy 8(4)
1189ndash1228 httpsdoiorg101007s13132-016-0417-1
The M M amp Usagawa T (2018) A comparative study of studentsrsquo readiness on e-learning education between Indonesia
and Myanmar American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS) 40(1)
113-124
Venkatraman N (1989) The concept of fit in strategy research Toward verbal and statistical correspondence Academy of
Management Review 9(3) 513-525 httpsdoiorg102307258177
Zuvic-Butorac M Nebic Z amp Nemcanin D (2011) Establishing an institutional framework for an e-learning
implementation Experiences from the University of Rijeka Croatia Journal of Information Technology Education
Innovations in Practice 10 43-56 httpsdoiorg10289451364
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Recommended Citation
-
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Cover Page Footnote
-
- tmp1624440487pdfGS9c9
-
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 195
student S3 revealed that ldquoa discussion policy for example may improve adoption of [TSL] because
once e-discussions are made they can compel one to use the [TSL] facilitiesrdquo The result from the
interview process on time to experiment with TSL conflicts with the cluster one whereby the majority
of the students never found time to practise with TSL facilities Shah and Cheng (2019) however
indicate that time influences the adoption of TSL facilities Quantitative findings in this cluster on
financial support could be related to those of student S3 who indicated that there was indirect financial
support by their university through the provision of wireless technology On the issue of management
commitment findings are in line with those of student S4 who felt that university management was
committed because they designed computer literacy sessions for them A typical student in this cluster
was 25 years old male by gender and in year 2 of study (see Table 5) This cluster (n = 42) had the
majority of the student respondents among the six clusters
The alignment of the configurational factors in Cluster 5 seemed to be lsquoweakerrsquo than that of Cluster 1
thus this cluster was ranked fourth Whereas the students in this cluster indicated lsquovery muchrsquo adoption
of TSL in some instances the configurational variables registered low scores For instance they had
very much acceptance of TSL environments yet they seemed not to be familiar with the TSL policy
The result on acceptance of TSL environments is parallel to that of Bond et al (2018) who indicated that
such environments are commonly used by students in higher education institutions in Germany The
result on the TSL policy was confirmed by student S4 who revealed that the TSL policy is not
effectively implemented in the university A normal student in this cluster was 26 years old male by
gender and in year 4 of the study (see Table 5) These students could be better adopters of TSL than
those of Clusters 3 and 6 because of their long-time experience with TSL as reflected in their year of
study compared to the said clusters (see Tables 4 and 5) It is not surprising this cluster had the best
distributions of ICTs among students
Similar to Cluster 5 Cluster 6 had 24 respondents (see Table 4) However students in this cluster are
coincidentally ranked as non-adopters of TSL among the six clusters (see Tables 4 and 5) This is
because there is no alignment between the configurational factors resulting in no adoption of TSL
These students were not willing to use IT could not modify their learning capabilities using IT and had
not realised the value of IT tools All 24 respondents in this cluster lsquoconcurredrsquo that the organization
never encouraged their use of TSL facilities This could imply that students were not involved at all
during the adoption of TSL Shah and Cheng (2019) reveal that students perceive that juggling work and
study caring for children financial difficulty and academic writing among other factors affect their
ability to adopt TSL On average students in this cluster were 26 years old male by gender and in year
1 of their study Being in their first year of study could imply that they had little experience with TSL
CONCLUSION
Identification of predictors of successful adoption of TSL among students was achieved using the
Gestalts approach Students perceived that organizational and individual factors predict successful
adoption of TSL Cluster 4 is the most coherent and as such adopted TSL most This is because the
organizational and individual factors were most aligned For example when students in this cluster are
financially supported and are in their second year of study they are eager to use to be innovative with
and embrace TSL And because of their eagerness innovativeness and ability to embrace TSL they have
accumulated more experience than others Cluster 6 students are non-adopters because they are more
inexperienced with TSL than the rest of the students
There seems to be a gap in the use of the non-linear techniques (eg clustering technique) in studies on
studentsrsquo perceptions Most studies for instance Chopra et al (2019) Gerasimova et al (2018) and Shah
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 196
and Cheng (2019) who have measured student perceptions have used linear techniques Thus this study
has closed this gap This study is a benchmark for universities in developing economies to integrate TSL
at university level For instance it should be noted that in order to achieve successful adoption of TSL
among students in universities management must be involved Nabushawo et al (2018) suggest that the
commitment of management can be achieved by collaborating with and training the users of TSL ISs
Since the world is challenged by Corona Virus Disease (COVID) this study can be used as model to
avail learning materials to students without spreading this disease
It should be noted that the rate of adoption of TSL among students is still low yet they have advanced in
age This contradicts Pereira et al (2018) who indicated that adoption of TSL usually takes place at an
early age It is therefore recommended that students should be supported to adopt TSL during their
earlier career years so that universities in Uganda can benefit from this innovation This can be done by
introducing TSL at primary level Universities need to strengthen their management capabilities such as
increasing the time studentsrsquo have to experiment with ICTs Further research is required to develop
strategies that can be adopted to enhance adoption of TSL among students at earlier ages Although this
study was carried out at a particular point in time it can also be carried out longitudinally There are
many indicators of the organization individual (student) and adoption of TSL besides those presented in
the conceptual framework Further research can be carried out on those Besides organization and
individual factors there is need to know the role of other factors in the adoption of TSL among students
While students from only two public universities were considered for this study students from other
universities can be considered as well
ACKNOWLEDGMENTS
The researchers want to thank the Almighty God for the gift of knowledge wisdom and understanding
in the writing of this paper The researchers also thank the Organization for Women in Science for the
Developing World (OWSD) and the Swedish International Development Agency (SIDA) for their
financial support in carrying out the study
REFERENCES
Acosta M L Sisley A Ross J Brailsford I Bhargava A Jacobs R amp Anstice N (2018) Student acceptance of e-
learning methods in the laboratory class in optometry PLOS ONE 13(12) 1-15
httpsdoiorg101371journalpone0209004
Adewole-Odeshi E (2014) Attitude of students towards e-learning in South-West Nigerian universities An application of
technology acceptance model Library Philosophy and Practice Article 1035
Angolia M G amp Pagliari L R (2016) Factors for successful evolution and sustainability of quality distance education
Online Journal of Distance Learning Administration 19(3)
Ayele B A amp Birhanie W K (2018) Acceptance and use of e-learning systems The case of teachers in technology
institutes of Ethiopian universities Applied Informatics 5(1) 1-11 httpsdoiorg101186s40535-018-0048-7
Back D A von Malotky J Sostmann K Peters H Hube R amp Hoff E (2019) Experiences with using e-learning tools
in orthopedics in an uncontrolled field study application Orthopaedics amp Traumatology Surgery amp Research
105(2) 389-393 httpsdoiorg101016jotsr201901002
Bhardwaj A amp Goundar S (2018) Students perspective of elearning and the future of education with MOOCs
International Journal of Computer Engineering 7(5) 248-260
Bhattacherjee A (2012) Social science research Principles methods and practices Textbooks Collection
httpscholarcommonsusfeduoa_textbooks3
Bond M Mariacuten V I Dolch C Bedenlier S amp Zawacki-Ritcher O (2018) Digital transformation in German higher
education Student and teacher perceptions and usage of digital media International Journal of Educational
Technology in Higher Education 15(48) httpsdoiorg101186s41239-018-0130-1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 197
Braun V amp Clarke V (2006) Using thematic analysis in psychology Qualitative Research in Psychology 33 77-101
Chopra G Madan P Jaisingh P amp Bhaskar P (2019) Effectiveness of e-learning portal from studentsrsquo perspective A
structural equation model (SEM) approach Interactive Technology and Smart Education 16(2) 94-116
httpsdoiorg101108ITSE-05-2018-0027
Creswell J W (2014) Research Design Qualitative quantitative and mixed methods approaches (4th ed) Sage
Publications
Damanpour F amp Schneider M (2006) Phases of the adoption of innovation in organisations Effects of environment
organisation and top managers British Journal of Management 17 215ndash236 httpsdoiorg101111j1467-
8551200600498x
Davis F D (1989) Perceived usefulness perceived ease of use and user acceptance of information technology MIS
Quarterly 13(3) 319ndash340 httpsdoiorg102307249008
Drazin R amp Van de Ven A H (1985) Alternative forms of fit in contingency theory Administrative Science Quarterly
30(4) 514-539 httpsdoiorg1023072392695
Drent M amp Meelissen M (2008) Which factors obstruct or stimulate teacher educators to use ICT innovatively
Computers amp Education 51 187ndash199 httpsdoiorg101016jcompedu200705001
Eze S C Chinedu-Eze V C amp Bello A O (2018) The utilisation of e-learning facilities in the educational delivery
system of Nigeria A study of M-University International Journal of Educational Technology in Higher Education
15 (34) 1-20 httpsdoiorg101186s41239-018-0116-z
Ferreira A Teixeira A L amp Dantas A R (2015) Non-technological innovation activities mediate the impacts of the
intra- and extra-organisational contexts on technological innovation outputs Enterprise and Work Innovation
Studies 11 9-43
Gerasimova V G Melamud M R Tutaeva D R Romanova Y D amp Zhenova N A (2018) The adoption of e-learning
technology at the Faculty of Distance Learning of Plekhanov Russian University of Economics Journal of Social
Studies Education Research 9(2) 172-188
Glazier R A Hamann K Pollock P H amp B Wilson B M (2019) Age gender and student success Mixing face-to-face
and online courses in political science Journal of Political Science Education 16(2) 142-157 httpsdoiorg1010801551216920181515636
Greene J C Caracelli V J amp Graham W F (1989) Toward a conceptual framework for mixed method evaluation
designs Educational Evaluation and Policy Analysis 11(3) 255-274 httpsdoiorg1023071163620
Gwamba G Renken J Nampijja J Mayende G amp Muyinda P B (2018) Contextualisation of e-learning systems in
higher education institutions In M Auer amp T Tsiatsos (Eds) Interactive mobile communication technologies and
learning Proceedings of the 11th IMCL conference (pp 44-55) Springer
Hardaker G amp Singh G (2011) The adoption and diffusion of eLearning in UK universities A comparative case study
using Giddenss theory of structuration Campus-Wide Information Systems 28(4) 221ndash233
httpsdoiorg10110810650741111162707
Kim H J Hong A J amp Song H (2019) The roles of academic engagement and digital readiness in studentsrsquo
achievements in university e-learning environments International Journal of Educational Technology in Higher
Education 16(21) 1-18 httpsdoiorg101186s41239-019-0152-3
Kimiloglu H Ozturan M amp Kutlu B (2017) Perceptions about and attitude toward the usage of e-learning in corporate
training Computers in Human Behavior 72 339-349 httpsdoiorg101016jchb201702062
Kisanga D amp Ireson G (2015) Barriers and strategies on adoption of e-learning in Tanzanian higher learning institutions
Lessons for adopters International Journal of Education and Development using Information and Communication
Technology (IJEDICT) 11(2) 126-137
Lee Y-K amp Pituch K (2002 December 10ndash13) Moderators in the adoption of e-learning An investigation of the role of
gender [Article] The Second International Conference on Electronic Business Taipei Taiwan
Lippman P C (2010) Can the physical environment have an impact on the learning environment CELE Exchange
httpsdoiorg1017875km4g21wpwr1-en
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 198
Maina M K amp Nzuki D M (2015) Adoption determinants of e-learning management system in institutions of higher
learning in Kenya A case of selected universities in Nairobi metropolitan International Journal of Business and
Social Science 6(2) 233ndash248
Martin M (1991) The culture of the telephone In PD Hopkins (Ed) Sexmachine Readings in culture gender and
technology (pp 50-74) Indiana University Press
Moakofhi M Leteane O Phiri T Pholele T amp Sebalatlheng P (2017) Challenges of introducing e-learning at
Botswana University of Agriculture and Natural Resources Lecturersrsquo perspective International Journal of
Education and Development using ICT 13( 2) 4-20
Nabushawo H M Muyinda P B Isabwe G M N Prinz A amp Mayende G (2018) Improving online interaction among
blended distance learners at Makerere University In M E Auer D Guralnick amp I Simonics (Eds) Advances in
Intelligent Systems and Computing (pp 63-69) Springer httpsdoiorg101007978-3-319-73210-7_8
Odewumi M O Yusuf M O amp Oputa G O (2018) UTAUT model Intention to use social media for learning interactive
effect of postgraduate gender in South-West Nigeria International Journal of Education and Development using
Information and Communication Technology (IJEDICT) 14(3) 239-251
Okai-Ugbaje S Ardzejewska K amp Imran A (2020) Readiness roles and responsibilities of stakeholders for sustainable
mobile learning adoption in higher education Education Sciences 10(3) 49-69
httpsdoiorg103390educsci10030049
Ozkan S amp Koseler R (2009) Multi-dimensional studentsrsquo evaluation of e-learning systems in the higher education
context An empirical investigation Computers amp Education 53(4) 1285ndash1296
httpsdoiorg101016jcompedu200906011
Parlakkılıccedil A (2014) Change management in transition to e-learning system Qualitative and Quantitative Methods in
Libraries 3(3) 637ndash651
Pereira A Martins P Morgado L amp Fonseca B (2018) Technological proposal using virtual worlds to support
entrepreneurship education for primary school children In M E Auer D Guralnick amp I Simonics (Eds)
Advances in Intelligent Systems and Computing (pp 124-132) Springer
Ramiacuterez-Correa P E Arenas-Gaitaacuten J amp Rondaacuten-Cataluntildea F J (2015) Gender and acceptance of e-learning A multi-
group analysis based on a structural equation model among college students in Chile and Spain PLOS ONE
10(10) 1-17 httpsdoiorg101371journalpone0140460
Rhema A amp Miliszewska I (2014) Analysis of student attitudes towards e-learning The case of engineering students in
Libya Issues in Informing Science and Information Technology 11 169-190 httpsdoiorg10289451987
Rogers E M (2003) Diffusion of innovations (5th ed) Free Press
Salinas J (2004) Cambios metodoloacutegicos con las TIC Estrategias didaacutecticas y entornos virtuales de ensentildeanza-aprendizaje
Bordoacuten 56(3-4) 469-481
Selim H M (2007) Critical success factors for e-learning acceptance Confirmatory factor models Computers amp
Education 49(2) 396ndash413 httpsdoi101016jcompedu200509004
Shah M amp Cheng M (2019) Exploring factors impacting student engagement in open access courses Open learning The
Journal of Open Distance and E-Learning 34(2) 187-202 httpsdoiorg1010800268051320181508337
Singh G ODonoghue J amp Worton H (2005) A study into the effects of elearning on higher education Journal of
University Teaching and Learning Practice 2(1) 13-24
Tchamyou V S (2017) The role of knowledge economy in African business Journal of the Knowledge Economy 8(4)
1189ndash1228 httpsdoiorg101007s13132-016-0417-1
The M M amp Usagawa T (2018) A comparative study of studentsrsquo readiness on e-learning education between Indonesia
and Myanmar American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS) 40(1)
113-124
Venkatraman N (1989) The concept of fit in strategy research Toward verbal and statistical correspondence Academy of
Management Review 9(3) 513-525 httpsdoiorg102307258177
Zuvic-Butorac M Nebic Z amp Nemcanin D (2011) Establishing an institutional framework for an e-learning
implementation Experiences from the University of Rijeka Croatia Journal of Information Technology Education
Innovations in Practice 10 43-56 httpsdoiorg10289451364
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Recommended Citation
-
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Cover Page Footnote
-
- tmp1624440487pdfGS9c9
-
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 196
and Cheng (2019) who have measured student perceptions have used linear techniques Thus this study
has closed this gap This study is a benchmark for universities in developing economies to integrate TSL
at university level For instance it should be noted that in order to achieve successful adoption of TSL
among students in universities management must be involved Nabushawo et al (2018) suggest that the
commitment of management can be achieved by collaborating with and training the users of TSL ISs
Since the world is challenged by Corona Virus Disease (COVID) this study can be used as model to
avail learning materials to students without spreading this disease
It should be noted that the rate of adoption of TSL among students is still low yet they have advanced in
age This contradicts Pereira et al (2018) who indicated that adoption of TSL usually takes place at an
early age It is therefore recommended that students should be supported to adopt TSL during their
earlier career years so that universities in Uganda can benefit from this innovation This can be done by
introducing TSL at primary level Universities need to strengthen their management capabilities such as
increasing the time studentsrsquo have to experiment with ICTs Further research is required to develop
strategies that can be adopted to enhance adoption of TSL among students at earlier ages Although this
study was carried out at a particular point in time it can also be carried out longitudinally There are
many indicators of the organization individual (student) and adoption of TSL besides those presented in
the conceptual framework Further research can be carried out on those Besides organization and
individual factors there is need to know the role of other factors in the adoption of TSL among students
While students from only two public universities were considered for this study students from other
universities can be considered as well
ACKNOWLEDGMENTS
The researchers want to thank the Almighty God for the gift of knowledge wisdom and understanding
in the writing of this paper The researchers also thank the Organization for Women in Science for the
Developing World (OWSD) and the Swedish International Development Agency (SIDA) for their
financial support in carrying out the study
REFERENCES
Acosta M L Sisley A Ross J Brailsford I Bhargava A Jacobs R amp Anstice N (2018) Student acceptance of e-
learning methods in the laboratory class in optometry PLOS ONE 13(12) 1-15
httpsdoiorg101371journalpone0209004
Adewole-Odeshi E (2014) Attitude of students towards e-learning in South-West Nigerian universities An application of
technology acceptance model Library Philosophy and Practice Article 1035
Angolia M G amp Pagliari L R (2016) Factors for successful evolution and sustainability of quality distance education
Online Journal of Distance Learning Administration 19(3)
Ayele B A amp Birhanie W K (2018) Acceptance and use of e-learning systems The case of teachers in technology
institutes of Ethiopian universities Applied Informatics 5(1) 1-11 httpsdoiorg101186s40535-018-0048-7
Back D A von Malotky J Sostmann K Peters H Hube R amp Hoff E (2019) Experiences with using e-learning tools
in orthopedics in an uncontrolled field study application Orthopaedics amp Traumatology Surgery amp Research
105(2) 389-393 httpsdoiorg101016jotsr201901002
Bhardwaj A amp Goundar S (2018) Students perspective of elearning and the future of education with MOOCs
International Journal of Computer Engineering 7(5) 248-260
Bhattacherjee A (2012) Social science research Principles methods and practices Textbooks Collection
httpscholarcommonsusfeduoa_textbooks3
Bond M Mariacuten V I Dolch C Bedenlier S amp Zawacki-Ritcher O (2018) Digital transformation in German higher
education Student and teacher perceptions and usage of digital media International Journal of Educational
Technology in Higher Education 15(48) httpsdoiorg101186s41239-018-0130-1
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 197
Braun V amp Clarke V (2006) Using thematic analysis in psychology Qualitative Research in Psychology 33 77-101
Chopra G Madan P Jaisingh P amp Bhaskar P (2019) Effectiveness of e-learning portal from studentsrsquo perspective A
structural equation model (SEM) approach Interactive Technology and Smart Education 16(2) 94-116
httpsdoiorg101108ITSE-05-2018-0027
Creswell J W (2014) Research Design Qualitative quantitative and mixed methods approaches (4th ed) Sage
Publications
Damanpour F amp Schneider M (2006) Phases of the adoption of innovation in organisations Effects of environment
organisation and top managers British Journal of Management 17 215ndash236 httpsdoiorg101111j1467-
8551200600498x
Davis F D (1989) Perceived usefulness perceived ease of use and user acceptance of information technology MIS
Quarterly 13(3) 319ndash340 httpsdoiorg102307249008
Drazin R amp Van de Ven A H (1985) Alternative forms of fit in contingency theory Administrative Science Quarterly
30(4) 514-539 httpsdoiorg1023072392695
Drent M amp Meelissen M (2008) Which factors obstruct or stimulate teacher educators to use ICT innovatively
Computers amp Education 51 187ndash199 httpsdoiorg101016jcompedu200705001
Eze S C Chinedu-Eze V C amp Bello A O (2018) The utilisation of e-learning facilities in the educational delivery
system of Nigeria A study of M-University International Journal of Educational Technology in Higher Education
15 (34) 1-20 httpsdoiorg101186s41239-018-0116-z
Ferreira A Teixeira A L amp Dantas A R (2015) Non-technological innovation activities mediate the impacts of the
intra- and extra-organisational contexts on technological innovation outputs Enterprise and Work Innovation
Studies 11 9-43
Gerasimova V G Melamud M R Tutaeva D R Romanova Y D amp Zhenova N A (2018) The adoption of e-learning
technology at the Faculty of Distance Learning of Plekhanov Russian University of Economics Journal of Social
Studies Education Research 9(2) 172-188
Glazier R A Hamann K Pollock P H amp B Wilson B M (2019) Age gender and student success Mixing face-to-face
and online courses in political science Journal of Political Science Education 16(2) 142-157 httpsdoiorg1010801551216920181515636
Greene J C Caracelli V J amp Graham W F (1989) Toward a conceptual framework for mixed method evaluation
designs Educational Evaluation and Policy Analysis 11(3) 255-274 httpsdoiorg1023071163620
Gwamba G Renken J Nampijja J Mayende G amp Muyinda P B (2018) Contextualisation of e-learning systems in
higher education institutions In M Auer amp T Tsiatsos (Eds) Interactive mobile communication technologies and
learning Proceedings of the 11th IMCL conference (pp 44-55) Springer
Hardaker G amp Singh G (2011) The adoption and diffusion of eLearning in UK universities A comparative case study
using Giddenss theory of structuration Campus-Wide Information Systems 28(4) 221ndash233
httpsdoiorg10110810650741111162707
Kim H J Hong A J amp Song H (2019) The roles of academic engagement and digital readiness in studentsrsquo
achievements in university e-learning environments International Journal of Educational Technology in Higher
Education 16(21) 1-18 httpsdoiorg101186s41239-019-0152-3
Kimiloglu H Ozturan M amp Kutlu B (2017) Perceptions about and attitude toward the usage of e-learning in corporate
training Computers in Human Behavior 72 339-349 httpsdoiorg101016jchb201702062
Kisanga D amp Ireson G (2015) Barriers and strategies on adoption of e-learning in Tanzanian higher learning institutions
Lessons for adopters International Journal of Education and Development using Information and Communication
Technology (IJEDICT) 11(2) 126-137
Lee Y-K amp Pituch K (2002 December 10ndash13) Moderators in the adoption of e-learning An investigation of the role of
gender [Article] The Second International Conference on Electronic Business Taipei Taiwan
Lippman P C (2010) Can the physical environment have an impact on the learning environment CELE Exchange
httpsdoiorg1017875km4g21wpwr1-en
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 198
Maina M K amp Nzuki D M (2015) Adoption determinants of e-learning management system in institutions of higher
learning in Kenya A case of selected universities in Nairobi metropolitan International Journal of Business and
Social Science 6(2) 233ndash248
Martin M (1991) The culture of the telephone In PD Hopkins (Ed) Sexmachine Readings in culture gender and
technology (pp 50-74) Indiana University Press
Moakofhi M Leteane O Phiri T Pholele T amp Sebalatlheng P (2017) Challenges of introducing e-learning at
Botswana University of Agriculture and Natural Resources Lecturersrsquo perspective International Journal of
Education and Development using ICT 13( 2) 4-20
Nabushawo H M Muyinda P B Isabwe G M N Prinz A amp Mayende G (2018) Improving online interaction among
blended distance learners at Makerere University In M E Auer D Guralnick amp I Simonics (Eds) Advances in
Intelligent Systems and Computing (pp 63-69) Springer httpsdoiorg101007978-3-319-73210-7_8
Odewumi M O Yusuf M O amp Oputa G O (2018) UTAUT model Intention to use social media for learning interactive
effect of postgraduate gender in South-West Nigeria International Journal of Education and Development using
Information and Communication Technology (IJEDICT) 14(3) 239-251
Okai-Ugbaje S Ardzejewska K amp Imran A (2020) Readiness roles and responsibilities of stakeholders for sustainable
mobile learning adoption in higher education Education Sciences 10(3) 49-69
httpsdoiorg103390educsci10030049
Ozkan S amp Koseler R (2009) Multi-dimensional studentsrsquo evaluation of e-learning systems in the higher education
context An empirical investigation Computers amp Education 53(4) 1285ndash1296
httpsdoiorg101016jcompedu200906011
Parlakkılıccedil A (2014) Change management in transition to e-learning system Qualitative and Quantitative Methods in
Libraries 3(3) 637ndash651
Pereira A Martins P Morgado L amp Fonseca B (2018) Technological proposal using virtual worlds to support
entrepreneurship education for primary school children In M E Auer D Guralnick amp I Simonics (Eds)
Advances in Intelligent Systems and Computing (pp 124-132) Springer
Ramiacuterez-Correa P E Arenas-Gaitaacuten J amp Rondaacuten-Cataluntildea F J (2015) Gender and acceptance of e-learning A multi-
group analysis based on a structural equation model among college students in Chile and Spain PLOS ONE
10(10) 1-17 httpsdoiorg101371journalpone0140460
Rhema A amp Miliszewska I (2014) Analysis of student attitudes towards e-learning The case of engineering students in
Libya Issues in Informing Science and Information Technology 11 169-190 httpsdoiorg10289451987
Rogers E M (2003) Diffusion of innovations (5th ed) Free Press
Salinas J (2004) Cambios metodoloacutegicos con las TIC Estrategias didaacutecticas y entornos virtuales de ensentildeanza-aprendizaje
Bordoacuten 56(3-4) 469-481
Selim H M (2007) Critical success factors for e-learning acceptance Confirmatory factor models Computers amp
Education 49(2) 396ndash413 httpsdoi101016jcompedu200509004
Shah M amp Cheng M (2019) Exploring factors impacting student engagement in open access courses Open learning The
Journal of Open Distance and E-Learning 34(2) 187-202 httpsdoiorg1010800268051320181508337
Singh G ODonoghue J amp Worton H (2005) A study into the effects of elearning on higher education Journal of
University Teaching and Learning Practice 2(1) 13-24
Tchamyou V S (2017) The role of knowledge economy in African business Journal of the Knowledge Economy 8(4)
1189ndash1228 httpsdoiorg101007s13132-016-0417-1
The M M amp Usagawa T (2018) A comparative study of studentsrsquo readiness on e-learning education between Indonesia
and Myanmar American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS) 40(1)
113-124
Venkatraman N (1989) The concept of fit in strategy research Toward verbal and statistical correspondence Academy of
Management Review 9(3) 513-525 httpsdoiorg102307258177
Zuvic-Butorac M Nebic Z amp Nemcanin D (2011) Establishing an institutional framework for an e-learning
implementation Experiences from the University of Rijeka Croatia Journal of Information Technology Education
Innovations in Practice 10 43-56 httpsdoiorg10289451364
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Recommended Citation
-
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Cover Page Footnote
-
- tmp1624440487pdfGS9c9
-
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 197
Braun V amp Clarke V (2006) Using thematic analysis in psychology Qualitative Research in Psychology 33 77-101
Chopra G Madan P Jaisingh P amp Bhaskar P (2019) Effectiveness of e-learning portal from studentsrsquo perspective A
structural equation model (SEM) approach Interactive Technology and Smart Education 16(2) 94-116
httpsdoiorg101108ITSE-05-2018-0027
Creswell J W (2014) Research Design Qualitative quantitative and mixed methods approaches (4th ed) Sage
Publications
Damanpour F amp Schneider M (2006) Phases of the adoption of innovation in organisations Effects of environment
organisation and top managers British Journal of Management 17 215ndash236 httpsdoiorg101111j1467-
8551200600498x
Davis F D (1989) Perceived usefulness perceived ease of use and user acceptance of information technology MIS
Quarterly 13(3) 319ndash340 httpsdoiorg102307249008
Drazin R amp Van de Ven A H (1985) Alternative forms of fit in contingency theory Administrative Science Quarterly
30(4) 514-539 httpsdoiorg1023072392695
Drent M amp Meelissen M (2008) Which factors obstruct or stimulate teacher educators to use ICT innovatively
Computers amp Education 51 187ndash199 httpsdoiorg101016jcompedu200705001
Eze S C Chinedu-Eze V C amp Bello A O (2018) The utilisation of e-learning facilities in the educational delivery
system of Nigeria A study of M-University International Journal of Educational Technology in Higher Education
15 (34) 1-20 httpsdoiorg101186s41239-018-0116-z
Ferreira A Teixeira A L amp Dantas A R (2015) Non-technological innovation activities mediate the impacts of the
intra- and extra-organisational contexts on technological innovation outputs Enterprise and Work Innovation
Studies 11 9-43
Gerasimova V G Melamud M R Tutaeva D R Romanova Y D amp Zhenova N A (2018) The adoption of e-learning
technology at the Faculty of Distance Learning of Plekhanov Russian University of Economics Journal of Social
Studies Education Research 9(2) 172-188
Glazier R A Hamann K Pollock P H amp B Wilson B M (2019) Age gender and student success Mixing face-to-face
and online courses in political science Journal of Political Science Education 16(2) 142-157 httpsdoiorg1010801551216920181515636
Greene J C Caracelli V J amp Graham W F (1989) Toward a conceptual framework for mixed method evaluation
designs Educational Evaluation and Policy Analysis 11(3) 255-274 httpsdoiorg1023071163620
Gwamba G Renken J Nampijja J Mayende G amp Muyinda P B (2018) Contextualisation of e-learning systems in
higher education institutions In M Auer amp T Tsiatsos (Eds) Interactive mobile communication technologies and
learning Proceedings of the 11th IMCL conference (pp 44-55) Springer
Hardaker G amp Singh G (2011) The adoption and diffusion of eLearning in UK universities A comparative case study
using Giddenss theory of structuration Campus-Wide Information Systems 28(4) 221ndash233
httpsdoiorg10110810650741111162707
Kim H J Hong A J amp Song H (2019) The roles of academic engagement and digital readiness in studentsrsquo
achievements in university e-learning environments International Journal of Educational Technology in Higher
Education 16(21) 1-18 httpsdoiorg101186s41239-019-0152-3
Kimiloglu H Ozturan M amp Kutlu B (2017) Perceptions about and attitude toward the usage of e-learning in corporate
training Computers in Human Behavior 72 339-349 httpsdoiorg101016jchb201702062
Kisanga D amp Ireson G (2015) Barriers and strategies on adoption of e-learning in Tanzanian higher learning institutions
Lessons for adopters International Journal of Education and Development using Information and Communication
Technology (IJEDICT) 11(2) 126-137
Lee Y-K amp Pituch K (2002 December 10ndash13) Moderators in the adoption of e-learning An investigation of the role of
gender [Article] The Second International Conference on Electronic Business Taipei Taiwan
Lippman P C (2010) Can the physical environment have an impact on the learning environment CELE Exchange
httpsdoiorg1017875km4g21wpwr1-en
Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 198
Maina M K amp Nzuki D M (2015) Adoption determinants of e-learning management system in institutions of higher
learning in Kenya A case of selected universities in Nairobi metropolitan International Journal of Business and
Social Science 6(2) 233ndash248
Martin M (1991) The culture of the telephone In PD Hopkins (Ed) Sexmachine Readings in culture gender and
technology (pp 50-74) Indiana University Press
Moakofhi M Leteane O Phiri T Pholele T amp Sebalatlheng P (2017) Challenges of introducing e-learning at
Botswana University of Agriculture and Natural Resources Lecturersrsquo perspective International Journal of
Education and Development using ICT 13( 2) 4-20
Nabushawo H M Muyinda P B Isabwe G M N Prinz A amp Mayende G (2018) Improving online interaction among
blended distance learners at Makerere University In M E Auer D Guralnick amp I Simonics (Eds) Advances in
Intelligent Systems and Computing (pp 63-69) Springer httpsdoiorg101007978-3-319-73210-7_8
Odewumi M O Yusuf M O amp Oputa G O (2018) UTAUT model Intention to use social media for learning interactive
effect of postgraduate gender in South-West Nigeria International Journal of Education and Development using
Information and Communication Technology (IJEDICT) 14(3) 239-251
Okai-Ugbaje S Ardzejewska K amp Imran A (2020) Readiness roles and responsibilities of stakeholders for sustainable
mobile learning adoption in higher education Education Sciences 10(3) 49-69
httpsdoiorg103390educsci10030049
Ozkan S amp Koseler R (2009) Multi-dimensional studentsrsquo evaluation of e-learning systems in the higher education
context An empirical investigation Computers amp Education 53(4) 1285ndash1296
httpsdoiorg101016jcompedu200906011
Parlakkılıccedil A (2014) Change management in transition to e-learning system Qualitative and Quantitative Methods in
Libraries 3(3) 637ndash651
Pereira A Martins P Morgado L amp Fonseca B (2018) Technological proposal using virtual worlds to support
entrepreneurship education for primary school children In M E Auer D Guralnick amp I Simonics (Eds)
Advances in Intelligent Systems and Computing (pp 124-132) Springer
Ramiacuterez-Correa P E Arenas-Gaitaacuten J amp Rondaacuten-Cataluntildea F J (2015) Gender and acceptance of e-learning A multi-
group analysis based on a structural equation model among college students in Chile and Spain PLOS ONE
10(10) 1-17 httpsdoiorg101371journalpone0140460
Rhema A amp Miliszewska I (2014) Analysis of student attitudes towards e-learning The case of engineering students in
Libya Issues in Informing Science and Information Technology 11 169-190 httpsdoiorg10289451987
Rogers E M (2003) Diffusion of innovations (5th ed) Free Press
Salinas J (2004) Cambios metodoloacutegicos con las TIC Estrategias didaacutecticas y entornos virtuales de ensentildeanza-aprendizaje
Bordoacuten 56(3-4) 469-481
Selim H M (2007) Critical success factors for e-learning acceptance Confirmatory factor models Computers amp
Education 49(2) 396ndash413 httpsdoi101016jcompedu200509004
Shah M amp Cheng M (2019) Exploring factors impacting student engagement in open access courses Open learning The
Journal of Open Distance and E-Learning 34(2) 187-202 httpsdoiorg1010800268051320181508337
Singh G ODonoghue J amp Worton H (2005) A study into the effects of elearning on higher education Journal of
University Teaching and Learning Practice 2(1) 13-24
Tchamyou V S (2017) The role of knowledge economy in African business Journal of the Knowledge Economy 8(4)
1189ndash1228 httpsdoiorg101007s13132-016-0417-1
The M M amp Usagawa T (2018) A comparative study of studentsrsquo readiness on e-learning education between Indonesia
and Myanmar American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS) 40(1)
113-124
Venkatraman N (1989) The concept of fit in strategy research Toward verbal and statistical correspondence Academy of
Management Review 9(3) 513-525 httpsdoiorg102307258177
Zuvic-Butorac M Nebic Z amp Nemcanin D (2011) Establishing an institutional framework for an e-learning
implementation Experiences from the University of Rijeka Croatia Journal of Information Technology Education
Innovations in Practice 10 43-56 httpsdoiorg10289451364
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
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- Recommended Citation
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- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
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- Cover Page Footnote
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Namirembe and Kyobe Successful Adoption of Technology Supported Learning in Universities
The African Journal of Information Systems Volume 13 Issue 2 Article 3 198
Maina M K amp Nzuki D M (2015) Adoption determinants of e-learning management system in institutions of higher
learning in Kenya A case of selected universities in Nairobi metropolitan International Journal of Business and
Social Science 6(2) 233ndash248
Martin M (1991) The culture of the telephone In PD Hopkins (Ed) Sexmachine Readings in culture gender and
technology (pp 50-74) Indiana University Press
Moakofhi M Leteane O Phiri T Pholele T amp Sebalatlheng P (2017) Challenges of introducing e-learning at
Botswana University of Agriculture and Natural Resources Lecturersrsquo perspective International Journal of
Education and Development using ICT 13( 2) 4-20
Nabushawo H M Muyinda P B Isabwe G M N Prinz A amp Mayende G (2018) Improving online interaction among
blended distance learners at Makerere University In M E Auer D Guralnick amp I Simonics (Eds) Advances in
Intelligent Systems and Computing (pp 63-69) Springer httpsdoiorg101007978-3-319-73210-7_8
Odewumi M O Yusuf M O amp Oputa G O (2018) UTAUT model Intention to use social media for learning interactive
effect of postgraduate gender in South-West Nigeria International Journal of Education and Development using
Information and Communication Technology (IJEDICT) 14(3) 239-251
Okai-Ugbaje S Ardzejewska K amp Imran A (2020) Readiness roles and responsibilities of stakeholders for sustainable
mobile learning adoption in higher education Education Sciences 10(3) 49-69
httpsdoiorg103390educsci10030049
Ozkan S amp Koseler R (2009) Multi-dimensional studentsrsquo evaluation of e-learning systems in the higher education
context An empirical investigation Computers amp Education 53(4) 1285ndash1296
httpsdoiorg101016jcompedu200906011
Parlakkılıccedil A (2014) Change management in transition to e-learning system Qualitative and Quantitative Methods in
Libraries 3(3) 637ndash651
Pereira A Martins P Morgado L amp Fonseca B (2018) Technological proposal using virtual worlds to support
entrepreneurship education for primary school children In M E Auer D Guralnick amp I Simonics (Eds)
Advances in Intelligent Systems and Computing (pp 124-132) Springer
Ramiacuterez-Correa P E Arenas-Gaitaacuten J amp Rondaacuten-Cataluntildea F J (2015) Gender and acceptance of e-learning A multi-
group analysis based on a structural equation model among college students in Chile and Spain PLOS ONE
10(10) 1-17 httpsdoiorg101371journalpone0140460
Rhema A amp Miliszewska I (2014) Analysis of student attitudes towards e-learning The case of engineering students in
Libya Issues in Informing Science and Information Technology 11 169-190 httpsdoiorg10289451987
Rogers E M (2003) Diffusion of innovations (5th ed) Free Press
Salinas J (2004) Cambios metodoloacutegicos con las TIC Estrategias didaacutecticas y entornos virtuales de ensentildeanza-aprendizaje
Bordoacuten 56(3-4) 469-481
Selim H M (2007) Critical success factors for e-learning acceptance Confirmatory factor models Computers amp
Education 49(2) 396ndash413 httpsdoi101016jcompedu200509004
Shah M amp Cheng M (2019) Exploring factors impacting student engagement in open access courses Open learning The
Journal of Open Distance and E-Learning 34(2) 187-202 httpsdoiorg1010800268051320181508337
Singh G ODonoghue J amp Worton H (2005) A study into the effects of elearning on higher education Journal of
University Teaching and Learning Practice 2(1) 13-24
Tchamyou V S (2017) The role of knowledge economy in African business Journal of the Knowledge Economy 8(4)
1189ndash1228 httpsdoiorg101007s13132-016-0417-1
The M M amp Usagawa T (2018) A comparative study of studentsrsquo readiness on e-learning education between Indonesia
and Myanmar American Scientific Research Journal for Engineering Technology and Sciences (ASRJETS) 40(1)
113-124
Venkatraman N (1989) The concept of fit in strategy research Toward verbal and statistical correspondence Academy of
Management Review 9(3) 513-525 httpsdoiorg102307258177
Zuvic-Butorac M Nebic Z amp Nemcanin D (2011) Establishing an institutional framework for an e-learning
implementation Experiences from the University of Rijeka Croatia Journal of Information Technology Education
Innovations in Practice 10 43-56 httpsdoiorg10289451364
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Recommended Citation
-
- Predictors of Successful Adoption of Technology Supported Learning in Universities in Uganda A Studentsrsquo Perspective
-
- Cover Page Footnote
-
- tmp1624440487pdfGS9c9
-